Taking No Chances: Opportunistic Screening’s Role in Early Lung Cancer Detection

Key Highlights

  • Over 20M Chest CTs are performed every year in the USA alone  
  • Every chest CT scan is a potential lung cancer screening opportunity 
  • Chest CT scanning increased significantly during the pandemic 
  • conducted a deep-learning study to use CT scans for COVID to screen for actionable nodules


Jackson Brown, Jr. once said that nothing is more expensive than a missed opportunity. Lung cancer is perhaps the ideal example of this because incidental/early detection via opportunistic screening can play a significant role in helping to successfully combat the malady. 

Lung cancer accounts for 1 in 5 cancer deaths yearly; the leading cause of cancer-related deaths worldwide. It accounts for the greatest economic and public health burden of all cancers annually; approximately $180 billion. This is also because the prognosis for lung cancer is poor compared to other cancers, largely due to a high proportion of cases being detected at an advanced stage  where treatment options are limited, and the 5-year survival rate is only 5-15%.The global pandemic strained healthcare systems worldwide also leading to significant increase in the chest CT volumes.  

“Earlier we would conduct approximately 300 chest CT scans per month. During the pandemic, this number rose to 7000 per month. It put a severe strain on doctors who must review every scan. Qure’s AI solution, qCT, made a significant difference to us by flagging missed actionable nodules on chest CT scans for further follow-ups & investigations.”
– Arpit Kothari, CEO,

The large volume of scans during the pandemic allowed to conduct a study using a deep-learning approach towards opportunistic screening for actionable lung nodules.


The study uses’s deep-learning approach to identify lung nodules on CT scans from patients who were scanned for COVID-19 from 5 radiology centers across different cities in India.  

The scans were sourced from, a leading radiology service provider in Central India and Aarthi Scans & Labs, yet another major diagnostic provider with 40 full-fledged diagnostic centers across India.

2502 scans were randomly selected from Chest CTs performed at 5 sites in two specialist radiology chains, Aarthi Scans and bodyScans during India’s 2nd and 3rd wave of Covid. They were processed by qCT, Qure’s AI capable of detecting and characterizing lung nodules. The radiologist report of the cases flagged by qCT were investigated for findings suggestive of cancer. Flagged cases for which the nodule was not reported were re-read by an independent radiologist with AI assistance on a web portal. They were asked to either confirm or reject the flag, rate the nodule for malignancy potential if confirmed or provide alternate finding if rejected (See Figure). 


  • 2502 CT scans were processed in total.  
  • Of these, 23.7% were flagged by qCT and re-read by an independent thoracic radiologist.  
  • In 19.4% of these flagged cases, the radiologist agreed that there were unreported actionable nodules.  
  • There were 19 cases where radiologists did not rule out the risk of malignancy and 2 out of these were rated as probably malignant.  


In the study,’s AI tool has assisted in reporting missed nodules which highlights the importance of opportunistic screening for identifying potential lung cancers early.  The need to improve efficiency and speed of clinical care continues to drive multiple innovations into practice, including AI. With the increasing demand for superior health care services and the large volumes of data generated daily from parallel streams, streamlining of clinical workflows has become a pressing issue. In our study, by using AI as a safety net, we found 21 chest CTs that should have warranted follow-up management for the patients. 

“Early detection plays a critical role in successfully treating Lung Cancer. Yet, there are several factors which contribute to the significant risk of these nodules getting missed in chest CT scans. Qure’s AI solution, qCT is immensely useful because it acts as a safety net; another pair of eyes to ensure that we clinicians can identify those patients who need immediate help. Eventually, AI can augment our efforts to defeat the disease.”
– Dr. Arunkumar Govindarajan, Director, Aarthi Scans & Labs

In Focus Uncategorized

Aarthi Scans: Scripting tele-radiology growth in India

The rapidly increasing need for radiology diagnostic and image interpretation services around the world has brought two major issues to light. The first is the lack of radiologists and the other is the dearth of specialized knowledge.

Building reliable communication and image transfer systems to tap into the expertise of radiologists who are not on-site can solve these issues to some extent. Hospitals, mobile imaging firms, urgent care clinics, and even some private practices all around the world are increasingly using tele-radiology. Tele-radiology improves patient care by allowing radiologists to provide services without having to be physically present at the imaging site so that the patients can receive round-the-clock access to trained specialists.

Tele-radiology is significantly less expensive than having a radiologist on-site. These services are typically priced per exam, with the cost as low as $1 per X-ray Tele-radiology has transformed the practice of many radiology clinics around the world, allowing them to provide results faster and by facilitating access to the radiologist, adding enormous value to the diagnostic process.

To set up a tele-radiology system between two centres, one requiring radiologist’s services and one providing radiologist’s services, the following elements are needed:

  1. Modality – a system that captures the medical image and has the facility to send these images in the preferred format i.e., DICOM
  2. PACS – a system that stores, sends, and receives medical images (DICOMs) and that can be identifiable by a unique address (like IP address, port number, etc.)
  3. Gateway – a medium that handles communication between the two centers (source and the destination) – receives the medical images from the source and sends back the output in the required format) using API calls. Complying with the data security and Protected Health Information (PHI) standards, de-identification and re-identification of confidential information can be performed by the Gateway.
  4. API Hub – a single place where all the Application Programming Interfaces (APIs) can be published and shared with external parties/clients by the intended service provider (tele-radiology) com

Introducing Aarthi Scans: India’s largest Tele-radiology service provider

India with its population of around 1.44 billion, right now we have around 1 radiologist for 100,000 people. Most rural India still lacks adequate radiological services and personnel, and not all imaging centers have subspecialty expertise, tele-radiology plays a significant role in quality diagnostics.

Aarthi Scans and Labs, one of the largest diagnostic centers were started in the year 2000 by Mr. Govindarajan. Today Aarthi Scans has more than 100+ branches across 10 states.It was in 2011 that they started their tele-radiology services to provide quick reporting for emergency cases and nighttime reporting and to ensure continuous reporting even when radiologists go on leave. Their radiologists' review over 200,000 CTs, 250,000 MRIs, and 2.1 million chest X-rays annually.

“At that point of time in 2011, when we started tele-radiology, telemedicine as a concept had not evolved in India. Radiologists giving reports without being present at the scanning location was viewed with skepticism. But once the referring doctors started viewing the benefits of tele-radiology, like nighttime reports, subspecialty reporting, they were impressed. Radiologists also needed a lot of convincing to report tele-radiology images. We standardised and digitised patient history, records, improved communication channels between tele-radiologists and radiographer in scanning sites and there was a slow and steady adoption by the Radiologist community. Our PACS vendor – Mr Ravindran from Innowave Healthcare Technologies helped us a great deal in solving the workflow related issues and helping us choose the right technology for us.”

 Govindarajan, Aarthi Scans and Labs

Aarthi Scans has taken a step forward by incorporating Artificial Intelligence (AI) into their reporting procedure, demonstrating their commitment to staying on the cutting edge of technology. The ratio of one radiologist to more than 100,000 people in India has resulted from stress in radiology reporting, scan misreads and reporting delays. Any solution that might assist radiologists to relax and improve their productivity is always welcome at the technologically advanced setup at Aarthi Scans, and AI can be of immense value add in this scenario.'s qXR, a Chest X-ray interpretation software – a CE Class II certified product – has been installed in Aarthi Scans diagnostic centers. The most common application of qXR in this setting is for Radiologist assistance to triage any scans with abnormalities on the worklist. The images are scanned and interpreted in under a minute. All scans that qXR identifies some findings in, are saved as a draft in the radiology worklist for further assessment and reporting. The report is generated in a natural language, significantly reducing the typing time that constitutes a significant portion of the reporting time. The final report is released in 30% lesser time due to this triaging mechanism and reading assistance by qXR. is a leading solution provider and we validated a few solutions before choose  We chose qXR because the accuracy in categorising a study as normal or abnormal is very high (95%)!”.  “We have been using qXRin our day-to-day radiological practice across India in all our branches. We are huge fans of qXR's accuracy and utility.”

– Dr. Arunkumar Govindarajan, Director, Aarthi Scans and Labs

Technical Integration

Qure PACS gateway for acquiring the Chest X-rays is integrated with Freedom Nano PACS which is present in every center of Aarthi Scans. Each center is authenticated with a unique token for the transmission of the studies and their corresponding results. The end-to-end transmission is supported by API calls that communicate with the Qure API hub to send the studies to the qXR AI models for processing. The AI interpretations are sent back to Freedom Nano PACS, where the radiologist can view the result from the individual centers. API and back to Freedom Nano PACS, where the radiologist can view the result from the individual centers. API and https-based communication make the data secured even on the cloud.

Since partnering with Aarthi Scans four months ago, qXR has processed over 45,000 scans, triaging 55% of scans with abnormal findings. On a daily basis, qXR processes 200 chest X-rays.

Scans that are classified as normal by qXR can be evaluated by the radiologist more quickly, giving them more time to review the abnormal scans and cutting down on overall reporting time. This has led to a reduction in the TAT by 30%. The qXR Secondary Capture output also uses contours to localize anomalies in the lungs, enabling radiologists to recognize abnormalities more accurately, without spending as much time as a regular scan.

Finalising a Chest X-ray report as 'normal' is like passing through the valley of uncertainty for every Radiologist and qXR is like that friendly colleague who assists you with a second opinion / confirmation without bias. qXR saves our Radiologists' time and removes doubt while reporting.qXR has resulted in a 30% reduction in reporting time for our Radiologists.

– Dr. Aarthi, Director, Aarthi Scans and Labs

Insights into incorporating AI into the practice – Dr. Arunkumar Govindarajan

“Learning about basics of Artificial Intelligence (AI) has helped me a lot to understand the inner workings of AI and terminologies. To start and understand in deep about AI one can take Coursera courses like – “AI for Everyone" by Andrew Ng and “AI for Medical Diagnosis” by DeepLearningAI. There are a lot of AI solutions out there, one can research in google to find which will suit your patients' and radiologist's needs. Once you fix a good AI vendor –

  • do your own validation and provide transparent feedback
  • partner with a good IT & PACS vendor and fix a workflow suited to your organization's needs. AI integration into PACS takes a bit of effort from the AI and PACS vendor. Be present during the meetings to ease the process and quickly resolve doubts”

What's Next?

After successful operations with qXR in all our centers, we will be next deploying Qure’s AI solution, qER for detecting brain abnormalities from head CT scans.

“Time is Brain and quick qER report never goes in vain” Dr. Arunkumar Govindarajan, Director, Aarthi Scans and Labs


qScout – Strengthening Global Vaccine Programs

Why an agile monitoring and management system is the need of the hour

The world is seeing unprecedented times. Two relentless years of a pandemic is enough to break even the strongest healthcare systems, that along with the current efforts to ramp up vaccinations and clinical care has resulted in most countries public health system being strained or barely functional. Such accelerated development and roll out of multiple vaccines, is a first for any disease.It is important that each of these vaccines and its effects are monitored for substantial periods of time to understand short term and long-term effects on varying demographic and risk factor profiles of vaccine recipients.

What is Active Vaccine Safety Surveillance (AVSS)?

The traditional surveillance systems in most countries, rely heavily on health care providers to notify the adverse events. This is a passive surveillance system that helps in detecting unsolicited adverse events Vaccine Survey is another conventional method, but the disadvantage is that it usually is a cross sectional survey with only a one time follow up. One of the ways to augment these traditionalsurveillance systems is to empower the vaccine recipient using smartphone based digital tools. AVSS or Active Vaccine Safety Surveillance systems helps by proactively enrolling many vaccine recipients who are followed up for all minor and major adverse events. This can significantly alleviate the burdens off frontline workers, while capturing large amount of data, frequently and in a timely fashion. Besides allowing the healthcare systems to address immediate or delayed adverse events, this has the potential to monitor the health of the community in the long term as well.

Policy formulation has also been extremely difficult for governments and world organisations given the novelty of the disease. This solution could allow for faster data driven decision making empowering governments and policy makers in a way that only technology can.

Need for AVSS in Covid-19

Post Vaccine monitoring: Before COVID–19, vaccines used to be licensed after 4-15years of rigorous clinical trials. With the fast-tracked development of COVID-19 vaccines, there is a likelihood that some of the rare and long-term adverse events may have gone undetected in the clinical trials. Through AVSS via phone, the vaccine recipients can be monitored for a period ranging from 07 days up to 12 months, getting real time alerts for any serious adverse events following immunization (AEFI)or Adverse Events of Special Interest (AESI). By automating this process, we have successfully tracked the symptoms fast enough to be of actionable value; the healthcare worker getting involved only if necessary.

Large Data collection and Analysis: we need interoperable systems that can harmonise data from multiple sites, with a validated AI algorithm to measure the risk of AEFIs and their early indicators. The system will need to be agile and scalableto work in varying resource settings.

Country-level Surveillance: There must be a centralised dashboard for policy makersand regulatory authorities to visualize community vaccine uptake statistics, AEFI patterns and efficacies.

qScout for AVSS monitoring

qScout is’s Artificial Intelligence and NLP-powered solution that improves vaccine recipient’s experience while augmenting traditional surveillance systems forindividual’s health monitoring. It has a smartphone-based component for easy interaction between the recipient and public health professionals.

How can qScout be used for active surveillance and monitoring of vaccinees?

Step 1: Walk-in/registered individuals at COVID-19 vaccination sites will be enrolled using qScout EMR by recording the following details :

  • Personal Identifiers
  • Risk groups
  • Medication history
  • Name and details of the vaccine administered.

QScout monitor demo

Step 2: Once the enrollment is completed, the vaccinated person receives a message on the mobile for their consent. Follow-up messages will be sent for a set period to check for any adverse/unexpected symptoms (AEFIs or AESI). The person will also be reminded about the second dose. Every enrolled individual will be monitored for a predefined period , as per the guidelines of the proposed project.

Step 3: Public health officials who have access to the data can see the analysis of the AEFIs OR AESIs on a real time dashboard The information will be segregated based on demographics, type of vaccine administered, count of individuals administered with dose 1 and/or dose 2 as well as percent drop-out between both the doses.

Benefits of Real-time remote patient monitoring after vaccination

  1. Early and timely detection and notification of serious AEFIs or AESIs
  2. Detection of rare and unknown adverse events, that may have not been detected during the clinical trials
  3. Recipient risk profiling and Predictive adverse events scoring or modelling
  4. Long term adverse effects of vaccination
  5. Identifying re-infection probabilities and severity
  6. Monitoring of Vaccine administration SOP adherence and Pharmacovigilance/ Post Market Surveillance for vaccine manufacturer

Prior Experience:

Country wide contact tracing and remote patient management: A Case Study

During the first wave of the COVID-19 pandemic, the qScout platform was adopted for national contact tracing and management mechanism by Ministry of Health in Oman. Within a span of a few weeks, qScout was integrated with Tarassud plus, the country’s ICT platform for surveillance and monitoring. qScout used AI chatbot customised to the local languages and engaged with confirmed cases capturing their primary and secondary symptoms. The AI engine analysed the information and provided insights enabling virtual triaging and timely escalation for medical requirements. Over a span of 8 moths, approximately 400,000 Covid-19 patients under quarantine in Oman regularly interacted with a software for over thousands of sessions taking off a significant proportion of healthcare workers’ burden. All this while the health authorities and government actively kept a watch centrally to monitor hotspot regions, areas needing additional resources and so on. Having qScout enabled with multi-lingual support in English as well as Arabic helped increase the ease of interaction for various users.

The software was deployed with a gadget that relayed instant reports to the competent authorities about the movements and locations that a quarantined or infected person visits. It also had the capability to send alerts if this person left their location or tried taking it off. This level of data collection allowed sharing relevant insights with the Ministry of Health about population level statistics vital for planning for resources. This coupled with’s qSCOUT, was a true exemplar of use of technology to tackle the pandemic.

Way Forward:

There are multiple studies that are ongoing with regional and state governments as well as non-governmental organizations. qScout is designed as a platform for monitoring safety and efficacy of all adult and pediatric vaccines and medications.


Smarter City: How AI is enabling Mumbai battle COVID-19

When the COVID-19 pandemic hit Mumbai, one of the most densely populated cities in the world, the Municipal Corporation of Greater Mumbai (MCGM) promptly embraced newer technologies, while creatively utilising available resources. Here is a deeper dive into how the versatility of chest x-rays and Artificial Intelligence helped the financial capital of India in efforts to containing this pandemic.

The COVID-19 pandemic is one of the most demanding adversities that the present generation has had to witness and endure. The highly virulent novel Coronavirus has posed a challenge like no other to the most sophisticated healthcare systems world over. Given the brisk transmission, it was only a matter of time that the virus spread to Mumbai, the busiest city of India, with a population more than 1.5 times that of New York.

The resilient Municipal Corporation of Greater Mumbai (MCGM), swiftly sprang into action, devising multiple strategies to test, isolate, and treat in an attempt to contain the pandemic and avoid significant damage. Given the availability and effectiveness of chest x-rays, they were identified to be an excellent tool to rule-in cases that needed further testing to ensure that no suspected case was missed out. Though Mumbai saw a steep rise in cases more than any other city in India, MCGM’s efforts across various touchpoints in the city were augmented using Qure’s AI-based X-ray interpretation tool – qXR – and the extension of its capabilities and benefits.

In the latter half of June, MCGM launched the MISSION ZERO initiative, a public-private partnership supported by the Bill & Melinda Gates Foundation, Bharatiya Jain Sanghatana (BJS) and Desh Apnayen and CREDAI-MCHI. Mobile vans with qXR installed digital X-ray systems were stationed outside various quarantine centers in the city. Individuals identified to be at high-risk of COVID-19 infection by on-site physicians from various camps were directed to these vans for further examination. Based on the clinical and radiological indications of the individuals thus screened, they were requested to proceed for isolation, RT-PCR testing, or continue isolation in the quarantine facility. Our objective was to reduce the load on the centers by continuously monitoring patients and discharging those who had recovered, making room for new patients to be admitted, and ensuring optimal utilization of resources.

A patient being screen in a BJS van equipped with qXR

The approach adopted by MCGM was multi-pronged to ascertain that no step of the pandemic management process was overlooked:

  • Triaging of high-risk and vulnerable and increase in case-detection in a mass screening setting to contain community transmission (11.4% individuals screened)
  • Patient management in critical care units to manage mortality rates
  • Support the existing healthcare framework by launching MISSION ZERO initiative and using chest X-ray based screening for optimum utilization of beds at quarantine centers

Learn more about qXR COVID in our detailed blog here

Triaging and Improvement in Case Finding

Kasturba Hospital and HBT Trauma Center were among the first few COVID-19 testing centers in Mumbai. However, due to the overwhelming caseload, it was essential that they triage individuals flowing into fever clinics for optimal utilization of testing kits.  The two centers used conventional analog film-based X-ray machines, one for standard OPD setting and another portable system for COVID isolation wards

From early March, both these hospitals adopted

  1. qXR software – our AI-powered chest X-ray interpretation tool provided the COVID-19 risk score based on the condition of the patient’s lungs
  2. qTrack – our newly launched disease management platform

The qTrack mobile app is a simple, easy to use tool that interfaces qXR results with the user. The qTrack app digitizes film-based X-rays and provides real-time interpretation using deep learning models. The x-ray technician simply clicks a picture of the x-ray against a view box via the app to receive the AI reading corresponding to the x-ray uploaded. The app is a complete workflow management tool, with the provision to register patients and capture all relevant information along with the x-ray. The attending physicians and the hospital Deans were provided separate access to the Qure portal so that they could instantly access AI analyses of the x-rays from their respective sites, from the convenience of their desktops/mobile phones.

qXR app in action at Kasturba Hospital

qXR app in action at Kasturba Hospital

Triaging in Hotspots and Containment Zones

When the city went into lockdown along with the rest of the world as a measure to contain the spread of infection, social distancing guidelines were imposed across the globe. However, this is not a luxury that the second-most densely populated city in the world could always afford. It is not uncommon to have several families living in close quarters within various communities, easily making them high-risk areas and soon, containment zones. With more than 50% of the COVID-19 positive cases being asymptomatic cases, it was imperative to test aggressively. Especially in the densely populated areas to identify individuals who are at high-risk of infection so that they could be institutionally quarantined in order to prevent and contain community transmission.

Workflow for COVID-19 management in containment zones using qXR

Workflow for COVID-19 management in containment zones using qXR

The BMC van involved in mass screenings and qXR in action in the van

The BMC van involved in mass screenings and qXR in action in the van

Patient Management in Critical Care Units

As the global situation worsened, the commercial capital of the country saw a steady rise in the number of positive cases. MCGM, very creatively and promptly, revived the previously closed down hospitals and converted large open grounds in the city into dedicated COVID-19 centers in record time with their own critical patient units. The BKC MMRDA grounds, NESCO grounds, NSCI (National Sports Council of India) Dome, and SevenHills Hospital are a few such centers.


The COVID-19 center at NESCO is a 3000-bed facility with 100+ ICU beds, catering primarily to patients from Mumbai’s slums. With several critical patients admitted here, it was important for Dr. Neelam Andrade, the facility head, and her team to monitor patients closely, keep a check on their disease progression and ensure that they acted quickly.  qXR helped Dr. Andrade’s team by providing instant automated reporting of the chest X-rays. It also captured all clinical information, enabling the center to make their process completely paperless.

The patient summary screen of qXR web portal

The patient summary screen of qXR web portal

“Since the patients admitted here are confirmed cases, we take frequent X-rays to monitor their condition. qXR gives instant results and this has been very helpful for us to make decisions quickly for the patient on their treatment and management.”

– Dr Neelam Andrade, Dean, NESCO COVID centre

SevenHills Hospital, Andheri

Located in the heart of the city’s suburbs, SevenHills Hospital was one of the first hospitals that were revived by MCGM as a part of COVID-19 response measures.

The center played a critical role on two accounts:

  1. Because patients were referred to the hospital for RT-PCR testing from door-to-door screening by MCGM. If found positive, they were admitted at the center itself for quarantine and treatment.
  2. With close to 1000 beds dedicated to COVID-19 patients alone, the doctors needed assistance for easy management of critical patients and to monitor their cases closely.

As with all COVID-19 cases, chest x-rays were taken of the admitted patients periodically to ascertain their lung condition and monitor the progress of the disease. All x-rays were then read by the head radiologist, Dr. Bhujang Pai, the next day, and released to the patient only post his review and approval. This meant that on most mornings, Dr. Pai was tasked with reading and reporting 200-250 x-rays, if not more. This is where qXR simplified his work.

Initially, we deployed the software on one of the two chest X-ray systems. However, after stellar feedback from Dr. Pai, our technology was installed in both the machines. In this manner AI, pre-read was available for all chest X-rays of COVID-19 patients from the center.

Where qXR adds most value:

  • several crucial indications are reported up by qXR
  • percentage lung affected helps to quantify improvement/deterioration in the patient lung and provide an objective assessment of the patient’s condition
  • pre-filled PDF report downloadable from the Qure portal makes it easier to finalize the radiology report prior to releasing to the patient, especially in a high-volume setting

Dr. Pai reviews and finalizes the qXR report prior to signing it off

Dr. Pai reviews and finalizes the qXR report prior to signing it off

“At SevenHills hospital, we have a daily load of ~220 Chest X-rays from the admitted COVID-19 cases, sometimes going up to 300 films per day. Having qXR has helped me immensely in reading them in a much shorter amount of time and helps me utilise my time more efficiently. The findings from the software are useful to quickly pickup the indications and we have been able to work with the team, and make suitable modifications in the reporting pattern, to make the findings more accurate. qXR pre-fills the report which I review and edit, and this facilitates releasing the patient reports in a much faster and efficient manner. This obviously translates into better patient care and treatment outcomes. The percentage of lung involvement which qXR analyses enhances the Radiologist’s report and is an excellent tool in reporting Chest radiographs of patients diagnosed with COVID infection.”

– Dr Bhujang Pai, Radiology Head, SevenHills Hospital

Challenges and learnings

During the course of the pandemic, Qure has assisted MCGM with providing AI analyses for thousands of chest x-rays of COVID-19 suspects and patients. This has been possible with continued collaboration with key stakeholders within MCGM who have been happy to assist in the process and provide necessary approvals and documentation to initiate work. However, different challenges were posed by the sites owing to their varied nature and the limitations that came with them.

We had to navigate through various technical challenges like interrupted network connections and lack of an IT team, especially at the makeshift COVID centers. We crossed these hurdles repeatedly to ensure that the x-rays from these centers were processed seamlessly within the stipulated timeframe, and the x-ray systems being used were serviced and functioning uninterrupted. Close coordination with the on-ground team and cooperation from their end was crucial to keep the engagement smooth.

This pandemic has been a revelation in many ways. In addition to reiterating that a virus sees no class or creed, it also forced us to move beyond our comfort zones and take our blinders off. Owing to limitations posed by the pandemic and subsequent movement restrictions, every single deployment of qXR by Qure was done entirely remotely. This included end-to-end activities like coordination with the key stakeholders, planning and execution of the deployment of the software, training of on-ground staff, and physicians using the portal/mobile app in addition to continuous operations support.

Robust and smart technology truly made it possible to implement what we had conceived and hoped for. Proving yet again that if we are to move ahead, it has to be a healthy partnership between technology and humanity.

Qure is supported by ACT Grants and India Health Fund for joining MCGM’s efforts for the pandemic response using qXR for COVID-19 management.


An AI Upgrade during COVID-19: Stories from the most resilient healthcare systems in Rural India

When the pandemic hit the world without discretion, it caused health systems to crumble across the world. While a large focus was on strengthening them in the urban cities, the rural areas were struggling to cope up. In this blog, we highlight our experience working with some of the best healthcare centers in rural India that are delivering healthcare to the last mile. We describe how they embraced AI technology during this pandemic, and how it made a difference in their workflow and patient outcomes.

2020 will be remembered as the year of the COVID-19 pandemic. Affecting every corner of the world without discretion, it has caused unprecedented chaos and put healthcare systems under enormous stress. The majority of COVID-19 transmissions take place due to asymptomatic or mildly symptomatic cases. While global public health programs have steadily created evolving strategies for integrative technologies for improved case detection, there is a critical need for consistent and rigorous testing. It is at this juncture that the impact of Qure’s AI-powered chest X-ray screening tool, qXR, was felt across large testing sites such as hospital networks and government-led initiatives.

In India, Qure joined forces with the Indian Government to combat COVID-19 and qXR found its value towards diagnostic aid and critical care management. With the assistance of investor groups like ACT Grants and India Health Fund, we extended support to a number of sites, strengthening the urban systems fighting the virus in hotspots and containment zones.
Unfortunately, by this time, the virus had already moved to the rural areas, crumbling the primary healthcare systems that were already overburdened and resource-constrained.

Discovering the undiscovered healthcare providers

Technologies are meant to improve the quality of human lives, and access to quality healthcare is one of the most basic necessities. To further our work with hospitals and testing centers across the world, we took upon ourselves if more hospitals could benefit from the software in optimising testing capability. Through our physicians, we reached out to healthcare provider networks and social impact organisations that could potentially use the software for triaging and optimisation. During this process, we discovered an entirely new segment, very different from the well equipped urban hospitals we have been operating so far, and interacted with few Physicians dedicated to delivering quality and affordable healthcare through these hospitals.

Working closely with the community public health systems, these secondary care hospitals act as a vital referral link for tertiary hospitals. Some of these are located in isolated tribal areas and address the needs of large catchment populations, hosting close to 100,000 OPD visits annually. They already faced the significant burden of TB and now had to cope with the COVID-19 crisis. With testing facilities often located far away, the diagnosis time increases by days, which is unfortunate because chest X-rays are crucial for primary investigation prior to confirmatory tests, mainly due to the limitations in a testing capacity. No, sufficient testing kits have not reached many parts of rural India as yet!

“I have just finished referring a 25-year-old who came in respiratory distress, flagged positive on X-ray with positive rapid antigen test to Silchar Medical College and Hospital (SMCH), which is 162kms away from here. The number of cases here in Assam is increasing”

Dr. Roshine Koshy, Makunda Christian Leprosy and General Hospital in Assam.

BSTI algorithm

On the left: Chinchpada mission hospital, Maharashtra; Right: Shanti Bhavan Medical Center, Jharkhand.

When we first reached out to these hospitals, we were struck by the heroic vigour with which they were already handling the COVID-19 crisis despite their limited resources. We spoke to the doctors, care-givers and IT experts across all of these hospitals and they had the utmost clarity from the very beginning on how the technology could help them.

Why do they need innovations?

Patients regularly present with no symptoms or atypical ones and conceal their travel history due to the associated stigma of COVID-19. Owing to the ambiguous nature of the COVID-19 presentation, there is a possibility of missing subtle findings. This means that, apart from direct contact with the patient, it puts the healthcare team, their families, and other vulnerable patients at risk.

qXR bridges underlying gaps in these remote, isolated and resource-constrained regions around the world. Perhaps the most revolutionary, life-saving aspect is the fact that, in less than 1 minute, qXR generates the AI analysis of whether the X-ray is normal or abnormal, along with a list of 27+ abnormalities including COVID-19 and TB. With qXR’s assistance, the X-rays that are suggestive of a high risk of COVID-19 are flagged, enabling quick triaging and isolation of these suspects till negative RT PCR confirmatory results are received. As the prognosis changes with co-morbidities, alerting the referring Physician via phone of life-threatening findings like Pneumothorax is an added advantage.

Overview of results generated by qXR

Overview of results generated by qXR

Due to the lack of radiologists and other specialists in their own or neighbouring cities, Clinicians often play multiple roles – Physician, Obstetrician, Surgeon, Intensivist, Anaesthesist – and is normal in these hospitals that investigate, treat and perform surgeries for those in need. Detecting any case at risk prior to their surgical procedures are important for necessitating RT PCR confirmation and further action.

Enabling the solution and the impact

These hospitals have been in the service of the local communities with a mix of healthcare and community outreach services for decades now. Heavily dependent on funding, these setups have to often navigate severe financial crises in their mission to continue catering to people at the bottom of the pyramid. Amidst the tribal belt in Jharkhand, Dr. George Mathew (former Principal, CMC, Vellore) and Medical Director of Shantibhavan Medical Center in Simdega, had to face the herculean task of providing food and accommodation for all his healthcare and non-healthcare staff as they were ostracised by their families owing to the stigma attached to COVID-19 care. Lack of availability of  PPE kits and other protective gear, also pushed these sites to innovate and produce them inhouse.

Staff protecting themselves and patients

Left: the staff of Shanti Bhavan medical center making the essentials for protecting themselves in-house; Right: staff protecting themselves and a patient.

qXR was introduced to these passionate professionals and other staff were sensitized on the technology. Post their buy-in of the solution, we on-boarded 11 of these hospitals, working closely with their IT teams for secure protocols, deployment and training of the staff in a span of 2 weeks. A glimpse of the hospitals as below:

LocationHospital NameSetting
Betul District, rural Madhya PradeshPadhar HospitalThis is a 200 bedded multi-speciality charitable hospital engages in a host of community outreach activities in nearby villages involving education, nutrition, maternal and child health programs, mental health and cancer screening
Nandurbar, MaharashtraChinchpada Mission HospitalThis secondary care hospital serves the Bhil tribal community. Patients travel upto 200kms from the interiors of Maharashtra to avail affordable, high quality care.
Tezpur, AssamThe Baptist Christian HospitalThis is a 200- bedded secondary care hospital in the North eastern state of Assam
Bazaricherra, AssamMakunda Christian Leprosy & General HospitalThey cater to the tribal regions. Situated in a district with a Maternal Mortality Rate (MMR) as high as 284 per 100,000 live births and Infant Mortality Rate (IMR) of 69 per 1000 live births. They conduct 6,000 deliveries, and perform 3,000 surgeries annually.
Simdega, JharkhandShanti Bhavan Medical CenterThis secondary hospital caters to remote tribal district. It is managed entirely by 3-4 doctors that actively multitask to ensure highest quality care for their patients. The nearest tertiary care hospital is approximately 100 km away. Currently, they are a COVID-19 designated center and they actively see many TB cases as well.

Others include hospitals in Khariar, Odisha; Dimapur, Nagaland; Raxaul, Bihar and so on.

Initially, qXR was used to process X-rays of cases with COVID-19 like symptoms, with results interpreted and updated in a minute. Soon the doctors found it to be useful in OPD as well and the solution’s capability was extended to all patients who visited with various ailments that required chest X-ray diagnosis. Alerts on every suspect are provided immediately, based on the likelihood of disease predicted by qXR, along with information on other suggestive findings. The reports are compiled and integrated on our patient workflow management solution, qTrack. Due to resource constraints for viewing X-ray in dedicated workstations, the results are also made available real-time using the qTrack mobile application.

qTrack app and web

Left: qTrack app used by the Physicians to view results in real time during while they are attending patients and performing routine work; Right: qTrack web used by Physicians and technicians to view instantaneously for reporting.

“It is a handy tool for our junior medical officers in the emergency department, as it helps in quick clinical decision making. The uniqueness of the system being speed, accuracy, and the details of the report. We get the report moment the x rays are uploaded on the server. The dashboard is very friendly to use. It is a perfect tool for screening asymptomatic patients for RT PCR testing, as it calculates the COVID-19 risk score. This also helps us to isolate suspected patients early and thereby helping in infection control. In this pandemic, this AI system would be a valuable tool in the battleground”

Dr Jemin Webster, Tezpur Baptist Hospital

Once the preliminary chest X-ray screening is done, the hospitals equipped with COVID-19 rapid tests get them done right away, while the others send samples to the closest testing facility which may be more than 30 miles away, with results made available in 4-5 days or more. But, none of these hospitals have the RT-PCR testing facility, yet!

qXR Protocol

In Makunda Hospital, Assam, qXR is used as an additional input in the diagnosis methodologies to manage the patient as a COVID-19 patient. They have currently streamlined their workflow to include the X-ray technicians taking digital X-rays and uploading the images on qXR, to  follow up and alert the doctors. Meanwhile, physicians can also access reports, review images  and make clinical corroboration anywhere they are through qTrack and manage patients without any undue delay.

Dr. Roshine Koshy using qXR

Dr. Roshine Koshy using qXR system during her OPD to review and take next course of action

“One of our objectives as a clinical team has been to ensure that care for non-COVID-19 patients is not affected as much as possible as there are no other healthcare facilities providing similar care. We are seeing atypical presentations of the illness, patients without fever, with vague complaints. We had one patient admitted in the main hospital who was flagged positive on the qXR system and subsequently tested positive and referred to a higher center. All the symptomatic patients who tested positive on the rapid antigen test have been flagged positive by qXR and some of them were alerted because of the qXR input. Being a high volume center and the main service provider in the district, using as a triaging tool will have enormous benefits in rural areas especially where there are no well-trained doctors”

– Dr. Roshine Koshy, Makunda Christian Leprosy and General Hospital in Assam.

There are a number of changes our users experienced in this short span of introduction of qXR in their existing workflow including:

  • Empowering the front-line healthcare physicians and care-givers in quick decisions
  • Enabling diagnosis for patients by triaging them for Rapid Antigen or RT-PCR tests immediately
  • Identifying asymptomatic cases which would have been missed otherwise
  • Ensuring safety of the health workers and other staff
  • Reducing risk of disease transmission

In Padhar Hospital, Madhya Pradesh, in addition to triaging suspected COVID cases, qXR assists doctors in managing pre-operative patients, where their medicine department takes care of pre-anaesthesia checkups as well. qXR helps them in identifying and flagging off suspected cases who are planned for procedures.  They are deferred till diagnosis or handled with appropriate additional safety measures in case of an emergency.

“We are finding it quite useful since we get a variety of patients, both outpatients and inpatients. And anyone who has a short history of illness and has history suggestive of SARI, we quickly do the chest X-ray and if the Qure app shows a high COVID-19 score, we immediately refer the patient to the nearby district hospital for RT-PCR for further management. Through the app we are also able to pick up asymptomatic suspects who hides their travel history or positive cases who have come for second opinion, to confirm and/or guide them to the proper place for further testing and isolation”

– Dr Mahima Sonwani, Padhar Hospital, Betul, Madhya Pradesh

Dr. Roshine Koshy using qXR

Left: technician capturing X-ray in Shanti Bhavan medical center; Right: Dr. Jemine Webster using qXR solution in Baptist hospital, Tezpur

In some of the high TB burden settings like Simdega in Jharkhand, qXR is used as a surveillance tool for screening and triaging Tuberculosis cases in addition to COVID-19 and other lung ailments.

“We are dependent on chest X-rays to make the preliminary diagnosis in both these conditions before we perform any confirmatory test. There are no trained radiologists available in our district or our neighbouring district and struggle frequently to make accurate diagnosis without help of a trained radiologist. The AI solution provided by Qure, is a perfect answer for our problem in this remote and isolated region. I strongly feel that the adoption of AI for Chest X-ray and other radiological investigation is the ideal solution for isolated and human resource deprived regions of the world”

– Dr.George Mathew, Medical Director, Shanti Bhavan Medical Centre

Currently, qXR processes close to 150 chest X-rays a day from these hospitals, enabling quick diagnostic decisions for lung diseases.

Challenges: Several hospitals had very basic technological infrastructure systems with poor internet connectivity and limitations in IT systems for using all supporting softwares. They were anxious about potential viruses / crashing the computer where our software was installed. Most of these teams had limited understanding of exposure to working with such softwares as well. However, they were extremely keen to learn, adapt and even provide solutions to overcome these infrastructural limitations. The engineers of the customer success team at Qure, deployed the software gateways carefully, ensuring no interruption in their existing functioning.


At Qure, we have worked closely with public health stakeholders in recent years. It is rewarding to hear the experiences and stories of impact from these physicians. To strengthen their armor in the fight against the pandemic even in such resource-limited settings, we will continue to expand our software solutions. Without limitation, qXR will be available across primary, secondary, and tertiary hospitals. The meetings, deployments, and training will be done remotely, providing a seamless experience. It is reassuring to hear these words:

“Qure’s solution is particularly attractive because it is cutting edge technology that directly impacts care for those sections of our society who are deprived of many advances in science and technology simply because they never reach them! We hope that this and many more such innovative initiatives would be encouraged so that we can include the forgotten masses of our dear people in rural India in the progress enjoyed by those in the cities, where most of the health infrastructure and manpower is concentrated”

Dr. Ashita Waghmare, Chinchpada hospital

Democratizing healthcare through innovations! We will be publishing a detailed study soon.


Re-purposing qXR for COVID-19

In March 2020, we re-purposed our chest X-ray AI tool, qXR, to detect signs of COVID-19. We validated it on a test set of 11479 CXRs with 515 PCR-confirmed COVID-19 positives. The algorithm performs at an AUC of 0.9 (95% CI : 0.88 - 0.92) on this test set. At our most common operating threshold for this version, sensitivity is 0.912 (95% CI : 0.88 - 0.93) and specificity is 0.775 (95% CI : 0.77 - 0.78). qXR for COVID-19 is used at over 28 sites across the world to triage suspected patients with COVID-19 and to monitor the progress of infection in patients admitted to hospital

The emergence of the COVID-19 pandemic has already caused a great deal of disruption around the world. Healthcare systems are overwhelmed as we speak, in the face of WHO guidance to ‘test, test, test’ [1]. Many countries are facing a severe shortage of Reverse Transcription Polymerase Chain Reaction (RT-PCR) tests. There has been a lot of debate around the role of radiology — both chest X-rays (CXRs) and chest CT scans — as an alternative or supplement to RT-PCR in triage and diagnosis. Opinions on the subject range from ‘Radiology is fundamental in this process’ [2] to ‘framing CT as pivotal for COVID-19 diagnosis is a distraction during a pandemic, and possibly dangerous’ [3].

Role of Radiography

The humble chest X-ray has emerged as the frontline screening and diagnostic tool for COVID-19 infection in a few countries and is used in conjunction with clinical history and key blood markers such as C-Reactive Protein (CRP) test and lymphopenia [4]. Ground glass opacities and consolidations which are peripheral and bilateral in nature are attributed to be the most common findings with respect to COVID related infections on CXRs and chest CTs. CXRs can help in identifying COVID-19 related infections and can be used as a triage tool in most cases. In fact, Italian and British hospitals are employing CXR as a first-line triage tool due to high RT-PCR turnaround times. A recent study [5] which examined CXRs of 64 patients found that in 9% of cases, initial RT-PCR was negative whereas CXRs showed abnormalities. All these cases subsequently tested positive for RT-PCR within 48 hours. The American college of Radiology recommends considering portable chest X-rays [6] to avoid bringing patients to radiography rooms. The Canadian Association of Radiologists suggest the use of mobile chest X-ray units for preliminary diagnosis of suspected cases [7] and to monitor critically ill patients, but have reported that no abnormalities are seen on CXRs in the initial stages of the infection.

BSTI algorithm

Radiology decision tool for suspected COVID-19 – The British Society of Thoracic Imaging [8]

As of today, despite calls for opening up imaging data on COVID-19 and outstanding efforts from physicians on the front-lines, there are limited X-ray or CT datasets in the public domain pertaining specifically to COVID. These datasets remain insufficient to train an AI model for COVID-19 triage or diagnosis but are potentially useful in evaluating the model – provided the model hasn’t been trained on the same data sources.

Building and evaluating qXR for COVID-19

Over the last month, customers, collaborators, healthcare providers, NGOs, state and national governments have reached out to us for help with COVID detection on chest X-rays and CTs.

In response, we have adapted our tried-and-tested chest X-ray AI tool, qXR to identify findings related to COVID-19 infections. qXR is trained using a dataset of 2.5 million chest X-rays (that included bacterial and viral pneumonia and many other chest X-ray findings) and is currently deployed in over 28 countries. qXR detects the following findings that are indicative of COVID-19: Opacities and Consolidation with bilateral and peripheral distribution and the following findings that are contra-indicative of COVID-19: hilar enlargement, discrete pulmonary nodule, calcification, cavity and pleural effusion.

These CE-marked capabilities have been leveraged for a COVID-19 triage product that is highly sensitive to COVID-19 related findings. This version of qXR gives out the likelihood of a CXR being positive for COVID-19, called Covid-19 Risk. Covid-19 Risk is computed using a post processing algorithm which combines the model outputs for the above mentioned findings. The algorithm is tuned on a set of 300 COVID-19 positives and 300 COVID-19 negatives collected from India and Europe.

Most new qXR users for COVID-19 are using it as a triage tool, often in settings with limited diagnostic resources. This version of qXR also localizes and quantifies the affected region. This capability is being used to monitor the progression of infection and to evaluate response to treatment in new clinical studies.

qXR sample

Sample Output of qXR [9]

Evaluation of the algorithm

We have created an independent testset of 11479 CXRs to evaluate our algorithm. The WHO [10] recommends a confirmatory diagnosis of COVID-19 using Reverse-Transcriptase Polymerase Chain Reaction (RT-PCR) – a specialised Nucleic Acid Amplification Test (NAAT) which looks for unique signatures using primers designed for the COVID-19 RNA sequence. Positives in this test set are defined as any CXR that is acquired while the patient has tested positive on RT-PCR test based on sputum/ lower respiratory and or upper respiratory aspirates/throat swab samples for COVID-19. Negatives in this test set are defined as any CXR which was acquired before the first case of COVID-19 was discovered.

The size of the negative set relative to the positive set was set to match the available prevalence in the literature [11]. The test set has 515 positives and 10964 negatives. Negatives are sampled from an independent set 250,000 CXRs. Negative set has 1609 cases of bilateral opacity and 547 cases of pulmonary consolidation in it (findings which are indicative of COVID-19 on a CXR), where the final diagnosis is not COVID-19. Negative set also has 355 non-opacity related abnormalities. This allowed us to evaluate algorithms ability to detect non COVID-19 opacities and findings, and is used to suggest alternative possible etiology and rule out COVID-19. We have used Area under Receiver Operating Characteristic Curve (AUC) along with Sensitivity and Specificity at the operating point to evaluate the performance of our algorithm.


Number of scans11479
Other Abnormalities355

Test set demographics

A subset (1000 cases) of this test set was independently reviewed by radiologists to create pixel level annotations to localize opacity and consolidation. Localization and progression monitoring capability of qXR is validated by computing the Jaccard Index between algorithm output and radiologist annotations.


To detect signs of COVID-19, We have observed an AUC of 0.9 (95% CI: 0.88 - 0.92) on this test set. At the operating threshold, we have observed the sensitivity to be 0.912 (95% CI : 0.88 - 0.93) and specificity to be 0.775 (95% CI : 0.77 - 0.78). While there are no WHO guidelines yet for an imaging based triage tool for COVID, WHO recommends a minimum sensitivity and specificity of 0.9 and 0.7 for community screening tests for Tuberculosis [12], which is a deadly infectious disease in itself. We have observed a Jaccard index of 0.88 between qXR’s output and expert’s annotations.

ROC Curve

Receiver Operating Characteristic Curve

Deploying qXR for COVID-19

qXR is available as a web-api and can be deployed within minutes. Built using our learnings of deploying globally and remotely, it can interface with a variety of PACS and RIS systems, and is very intuitive to interpret. qXR can be used to triage suspect patients in resource constrained countries to make effective use of RT-PCR test kits. qXR is being used for screening and triage at multiple hospitals in India and Mexico.

San Raffaele Hospital in Milan, Italy has deployed qXR to monitor patients and to evaluate patient’s response to treatments. In Karachi, qXR powered mobile vans are being used at multiple sites to identify potential suspects early and thus reducing burden on the healthcare system.

qXR deployments

Timeline of qXR for COVID

In the UK, all the suspected COVID-19 patients presenting to the emergency department are undergoing blood tests and CXR [4]. This puts a tremendous amount of workload on already burdened radiologists as it becomes critical for radiologists to report the CXRs urgently. qXR, with its ability to handle huge workloads, provides significant value in such a scenario and thus reduce the burden on radiologists.

qXR can also be scaled for rapid and extensive population screening. Frontline clinicians are increasingly relying on chest X-rars to triage the sickest patients, while they await RT-PCR results. When there is high clinical suspicion for COVID-19 infection, the need for a patient with positive chest X-ray to get admitted in a hospital is conceivable. qXR can help solve this problem at scale.

qXR deployments

Impact of qXR for COVID-19

Work with us

With new evidence published every day, and evolving guidance and protocols adapting in suit for COVID-19, national responses globally remain fluid. Singapore, Taiwan and South Korea have shown that aggressive and proactive testing plays a crucial role in containing the spread of the disease. We believe qXR can play an important role in expanding screening in the community to help reduce the burden on healthcare systems. If you want to use qXR, please reach out to us.


  1. WHO Director-General’s opening remarks at the media briefing on COVID-19 – WHO, Accessed Apr 9, 2020.
  2. Imaging the coronavirus disease COVID-19 – Healthcare in Europe Website, Accessed Apr 9, 2020.
  3. Hope et al. A role for CT in COVID-19? What data really tell us so far – The Lancet, Mar 27, 2020
  4. Lessons from the frontline of the covid-19 outbreak – BMJ Blog, Accessed Apr 9, 2020.
  5. Wong et al. Frequency and Distribution of Chest Radiographic Findings in COVID-19 Positive Patients – Radiology, Mar 27, 2020.
  6. ACR Recommendations for the use of Chest Radiography and Computed Tomography (CT) for Suspected COVID-19 Infection – ACR, Accessed Apr 9, 2020.
  7. Lei et al. COVID-19 Infection: Early Lessons – Canadian Association of Radiologists Journal, Mar 12, 2020.
  8. Radiology decision tool for suspected COVID-19 – The British Society of Thoracic Imaging, Accessed Apr 9, 2020.
  9. Cohen et al. COVID-19 image data collection – arXiv:2003.11597, 2020
  10. Laboratory testing for 2019 novel coronavirus (2019-nCoV) in suspected human cases – WHO, Accessed Apr 9, 2020.
  11. Verity et al. Estimates of the severity of coronavirus disease 2019: a model-based analysis – The Lancet Infectious Diseases, Mar, 2020.
  12. High priority target product profiles for new tuberculosis diagnostics: report of a consensus meeting, tech. rep., World Health Organization, Apr 28-29, 2014.