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AI biomarkers, built for real-world impact and clinical trials. Meet us at ASCO 2026 | Booth #IH12.

Qure.ai Recognized Among TIME’s 100 Most Influential Companies of 2025

Qure.ai partners with Microsoft to increase access to its lung cancer detection and management suite in the U.S.

qTrack

Qure.ai today announced the promotion of Amy Casey, a former Microsoft and Nuance leader, to Executive Vice President of Sales for North America and the appointment of Malika Shrivastava, a former Google executive, as its first Chief Marketing Officer, strengthening its leadership team as the company scales its commercial operations to meet growing demand for healthcare AI in the United States.

The appointments reflect Qure.ai's continued investment in scaling its US business and strengthening the commercial capabilities needed to support growing demand for AI-powered healthcare solutions. With FDA clearances spanning 26 findings and a growing footprint in the United States, the company is expanding its leadership team as healthcare organizations increasingly adopt AI to improve clinical workflows, enable earlier diagnosis and address capacity constraints.

"Healthcare is entering a defining era where AI will fundamentally reshape how care is delivered, improving outcomes while addressing longstanding gaps in access and efficiency," said Prashant Warier, CEO and Co-founder of Qure.ai. "The United States represents one of our most important growth markets, and we are making deliberate investments in leadership to support our next phase of expansion. Amy brings extensive experience leading enterprise software sales across the US healthcare ecosystem, while Malika brings a proven track record of building brands and scaling businesses globally, including in the US market.” 

As Executive Vice President of Sales for North America, Casey, who joined Qure.ai a year ago, will lead Qure.ai's commercial strategy and customer engagement across the region. Casey has played a key role in expanding Qure.ai's presence in the United States and brings more than two decades of experience leading enterprise software sales, strategic account management and commercial growth across the US healthcare market. Prior to joining Qure.ai, she spent 16 years across Microsoft and Nuance, leading national accounts and helping health systems modernize clinical and operational workflows through technology adoption.

"Qure.ai is at the forefront of applying AI to solve some of healthcare's most pressing challenges, from early disease detection to population health management," said Casey. "I am excited to lead Qure.ai's US operations as the company delivers meaningful clinical impact at scale, and I look forward to partnering with health systems and healthcare organizations across North America to accelerate the adoption of AI solutions that deliver meaningful clinical and operational outcomes."

As Qure.ai's inaugural Chief Marketing Officer, Shrivastava will lead the company's global marketing organization, overseeing brand, communications, product marketing, and market development. She brings over 15 years of experience building and scaling iconic brands, launching new products, driving go-to-market strategy, and expanding businesses across markets and stages of growth. Prior to joining Qure.ai, she led growth and go-to-market strategy at Glance (InMobi Group), where she scaled the India business and spearheaded expansion into the United States. Earlier, she held marketing leadership roles at Google, shaping growth for products including Android, Play, Chrome, and Pixel, and at Procter &amp; Gamble, where she managed leading brands such as Always (Whisper) and Pampers across India and Southeast Asia.

Commenting on her appointment, Shrivastava said, "Qure.ai represents a rare combination of technological innovation, meaningful real-world impact, and a deeply mission-driven culture. As healthcare systems around the world increasingly adopt AI to improve access, quality, and efficiency of care, Qure is uniquely positioned to lead this transformation. I am excited to build on the strong foundation created by the team and help make Qure a brand that is not only recognized for its innovation, but deeply loved, trusted and respected by healthcare providers, partners, policymakers, and future talent globally." 

Qure.ai's AI solutions are deployed in more than 105 countries and have impacted over 45 million lives worldwide. In the United States, the company continues to expand its footprint and build strategic relationships across the healthcare ecosystem, supporting providers and industry partners in adopting AI at scale.

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Qure.ai Strengthens North America Leadership Team to Accelerate US Expansion

-             A new partnership will embed Qure.ai’s Aira health care co-pilot across Mozambique’s health system to help authorities identify emerging health patterns, address misinformation and translate community concerns into actionable insights.

VillageReach, an international non-profit organization rooted in Mozambique since 2000 and focused on improving access to quality health care for hard-to-reach communities, and Qure.ai, a global AI company innovating solutions in health care for early detection and care management, have partnered with Mozambique’s Ministry of Health to strengthen national pandemic preparedness.

Through a Gates Foundation grant focused on strengthening pandemic preparedness and resilient health systems, VillageReach will work with Mozambique’s Ministry of Health to enhance national early warning and emergency response mechanisms. Central to this initiative is the integration of Qure.ai’s Aira, an AI-powered health care co-pilot that assists health systems to digitize and interpret health information from primary health centers ( PHCs) and communities for faster emergency response planning.

Embedded within health information sources like AlôVida, Aira will help health authorities and emergency coordination mechanisms, including Mozambique’s Public Health Emergency Operations Center (PHEOC), to better detect emerging community concerns, understand patterns of misinformation and respond to potential public health risks earlier.

Through platforms like AlôVida and Mozambique Health Information System for Monitoring and Evaluation (SIS-MA), the PHEOC receives thousands of health queries from citizens across the country. These queries range from new symptom reporting and care-seeking questions to new disease concerns and other public health enquiries, including vaccine information. Historically, AlôVida has served primarily as a hotline, connecting communities to trusted health information and services.

“By integrating AI into trusted platforms like AlôVida, we are creating a more responsive system that listens to people in real time and translates their concerns into meaningful insights for decision-makers.” Said Rotafina Donco, Mozambique Country Director, VillageReach. “This partnership represents an important step toward strengthening community-centered health, ensuring that even the most remote voices help shape faster, more effective public health responses.”

By embedding AI directly into existing health platforms, these interactions can now also contribute to continuous population-level health monitoring. Aira will analyse the interactions at scale to identify emerging symptom patterns, detect unusual health trends and issue early warning signals that may otherwise remain fragmented across individual reports. This initiative will be a game-changer in identifying geographic clustering of symptoms, monitoring potential infectious disease risks, and prioritizing timely investigation and response efforts.

“Our experience working with public health systems globally has shown that meaningful AI must adapt to how health systems already function,” said Divya Gupta, Chief Business Officer for Global Health, Qure.ai. “We have partnered with health programs across diverse settings, including Mozambique, to help move from reactive response toward proactive preparedness. With Aira embedded within Mozambique’s healthcare system, this collaboration supports earlier understanding of risks and more informed public health decision making.”

Mozambique continues to face recurrent public health emergencies, including cyclones and cholera outbreaks, which place significant strain on health systems, particularly in rural and hard-to-reach regions. These recurring emergencies have disrupted health care services and highlighted the challenges of maintaining timely outbreak detection and response at a community level.

While existing surveillance systems largely depend on data reported through health care facilities, many early warning signals first emerge within communities through symptoms, concerns and information requests. In several instances, misinformation and limited access to trusted health information have affected care-seeking behaviour and vaccination uptake, underscoring the need for stronger channels connecting communities and health authorities. By strengthening the ability to capture and learn from these signals, this partnership aims to support faster, more coordinated decision-making during health emergencies and improve preparedness for future outbreaks.

For more details, please click here:&nbsp;https://www.qure.ai/aira

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 VillageReach and Qure.ai Partner to Strengthen Mozambique’s  AI-Enabled Pandemic Preparedness System

AstraZeneca Pharma India Limited today signed a Memorandum of Understanding (MoU) with the Government of Telangana to introduce AI-enabled lung cancer screening across public healthcare facilities in the state, powered by&nbsp;Qure.ai’s&nbsp;AI-driven chest X-ray solution. The collaboration aims to strengthen early detection and improve outcomes for patients in both urban and rural areas.&nbsp;

Lung cancer is among the most pressing public health challenges in India today. Patients flagged as&nbsp;high risk&nbsp;will be referred for confirmation tests or follow-up care. The initiative comes as lung cancer cases continue to rise in India, from approximately&nbsp;63,700 cases in 2015 to more than 81,200 in 2025, with about 80%-85% of patients being diagnosed at advanced stages, contributing to&nbsp;nearly 60,000&nbsp;deaths annually.&nbsp;The disease is also no longer confined to smokers: cases among non-smokers are rising by 30–40%, making broad, population-level detection efforts increasingly important.&nbsp;

Telangana reflects these national pressures acutely. The state is projected to record 46,762 new cancer cases among adults in 2026, rising to 47,314 by 2030—an estimated 13% increase by 2027. Women bear a disproportionate share, with 25,510 new cases expected this year compared to 21,252 in men. According to the Telangana Cancer Burden Profile 2026, published by ICMR-NCDIR, one in six women in Hyderabad faces the risk of developing cancer in her lifetime, while one in eight men is likely to receive a diagnosis before the age of 74. Low awareness, cost barriers, and limited access in rural areas compound the challenge, often delaying diagnosis until the disease has progressed beyond curative treatment.&nbsp;

Early detection fundamentally changes this equation. Screening programmes that&nbsp;identify&nbsp;lung cancer at earlier stages can enable curative therapies for a significantly larger proportion of patients, improving survival outcomes and reducing the overall burden on the health system.&nbsp;

Under the MoU, AstraZeneca will&nbsp;facilitate&nbsp;the deployment of&nbsp;Qure.ai’s&nbsp;AI-powered chest X-ray solution, integrated into routine workflows at public health facilities across Telangana. The technology helps&nbsp;clinicians&nbsp;flag high-risk pulmonary nodules—a predominant precursor of lung cancer,&nbsp;along with 29 other lung conditions. High-risk patients will be triaged for diagnostic confirmation or follow-up, enabling a stage shift in lung cancer detection. A similar model has already been adopted in Goa, Tamil Nadu, and Karnataka.&nbsp;

Dr. S. Sangeetha Satyanarayana, Commissioner, Health &amp; Family Welfare Directorate, Government of Telangana, said, “Telangana is&nbsp;witnessing&nbsp;a steady rise in cancer cases, and late diagnosis due to limited screening uptake&nbsp;remains&nbsp;a major challenge. This collaboration integrates technology into routine public healthcare to bridge gaps in access and capacity and reflects our continued focus on building a more proactive, future-ready health system.”&nbsp;

Praveen Rao&nbsp;Akkinepally, Country President &amp; Managing Director, AstraZeneca Pharma India Ltd., said,&nbsp;“We&nbsp;sincerely thank&nbsp;the Government of Telangana for spearheading this initiative. Early detection plays a defining role in improving cancer outcomes, particularly in diseases like lung cancer, where diagnosis often happens at advanced stages. At AstraZeneca, partnerships are part of our broader commitment to expanding access to innovative healthcare solutions in India. We believe such collaborations can drive meaningful impact by bringing early diagnosis closer to communities that need it the most.”&nbsp;

Sagar Sen, Senior Vice President,&nbsp;Global Life Sciences and Strategic Alliances, Qure.ai, said,&nbsp;“Early detection&nbsp;remains&nbsp;one of the most critical levers in improving lung cancer outcomes. Through this collaboration in Telangana, we are integrating AI into routine chest X-ray workflows to help clinicians&nbsp;identify&nbsp;high-risk cases earlier and prioritise them for&nbsp;timely&nbsp;follow-up.&nbsp;At Qure.ai, we build scalable public health&nbsp;solutions,&nbsp;and this initiative expands access to early diagnosis.”&nbsp;

The initiative is expected to roll out across 20 public health facilities, covering both urban and rural health systems. It includes training and upskilling of healthcare professionals to support effective and sustainable adoption, as well as infrastructure enhancements where needed to ensure seamless integration into the public health system.

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AstraZeneca Signs MoU with Telangana Government to Deploy Qure.ai-Powered Lung Cancer Screening in Public Hospitals

Results from a new study* presented at the American Roentgen Ray Society’s (ARRS) 2026 annual meeting in Pittsburgh, PA, examined the potential for AI to&nbsp;identify&nbsp;lung cancers initially missed on routine chest X-rays at a&nbsp;large&nbsp;US quaternary medical&nbsp;center.&nbsp;

&nbsp;It highlights the growing clinical value of AI as a safety net for chest radiograph interpretation using the FDA cleared AI solution&nbsp;qXR-LN from Qure.ai. The AI solution can detect lung nodules on chest X-rays&nbsp;(CXR), which may&nbsp;warrant&nbsp;further clinical evaluation. Finding lung cancer before it spreads can change the entire trajectory of patient care, increasing five-year survival&nbsp;rates,&nbsp;improving quality of life lived, and can be the difference between curative and palliative treatments.&nbsp;&nbsp;&nbsp;A retrospective study conducted at University Hospitals Cleveland Medical&nbsp;Center&nbsp;analyzed&nbsp;historical cases drawn from a resident education database&nbsp;maintained&nbsp;by its cardiothoracic radiology section. The dataset included chest X-rays performed more than three years earlier for unrelated clinical indications, in which no pulmonary nodule had been reported on the&nbsp;initial&nbsp;read.&nbsp;&nbsp;

These chest X-rays were later linked to patients who&nbsp;subsequently&nbsp;received a lung cancer diagnosis through other clinical pathways, with confirmation by CT imaging and biopsy. The study period covered cases&nbsp;identified&nbsp;between January 14, 2021, and March 6, 2025, with cough being the most common presenting symptom prompting later imaging investigation.&nbsp;

“Pulmonary nodules missed on chest radiographs&nbsp;remain&nbsp;a challenge&nbsp;in thoracic imaging,&nbsp;especially when findings are subtle, obscured by overlaying anatomy or reviewed in busy emergency or&nbsp;outpatient&nbsp;settings. Delayed recognition can allow&nbsp;small lesions&nbsp;to progress to more advanced-stage lung cancer&nbsp;when curative treatment&nbsp;options&nbsp;diminish,” states&nbsp;Amit Gupta,&nbsp;MD,&nbsp;Division Chief of Cardiothoracic Imaging and Modality Director of Diagnostic Radiography at University Hospitals Cleveland Medical&nbsp;Center. “This study is helping produce real-world evidence and confidence for the imaging community&nbsp;about embracing AI as a support tool and&nbsp;as a&nbsp;second set of eyes.”

“The significance of this study is&nbsp;highlighting the power&nbsp;of&nbsp;integrating AI-assisted interpretation into routine chest radiograph workflows in the US, which&nbsp;will&nbsp;substantially&nbsp;reduce&nbsp;missed diagnoses and improve&nbsp;early-stage&nbsp;lung cancer detection.&nbsp;This&nbsp;has the potential to give radiologists and pulmonologists a new powerful&nbsp;tool to save lives,” states&nbsp;Samir Shah, MD, Chief Medical&nbsp;Officer&nbsp;at Qure.ai.&nbsp;&nbsp;&nbsp;

*Evaluation of an FDA-Approved AI Algorithm for Missed Lung Cancer Detection on Chest Radiographs. Natally&nbsp;AlArab, Syed Muhammad Awais Bukhari,&nbsp;Sreyes&nbsp;Venkatesh, Kianoush&nbsp;AnsariGilani, Amit Gupta&nbsp;

Presented at ARRS 2026&nbsp;April 12-15,&nbsp;Pittsburgh, PA,&nbsp;US.&nbsp;&nbsp;

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FDA-cleared chest x-ray AI shows great promise in missed lung cancer detection

Latest solution identifies, highlights &amp; categorizes key positive findings to support clinicians, taking total FDA cleared indications to 26

The US Food and Drug Administration (FDA) has given 510(k) Class II clearance of qXR-Detect, the latest computer-assisted detection (CADe) radiography solution from global AI company&nbsp;<a href="https://www.qure.ai/us">Qure.ai</a>.&nbsp;It powers the early identification, highlighting and categorizing of key positive findings on plain film chest X-rays to support emergency room (ER) physicians, family medicine practitioners and radiologists.

Chest radiography is the most performed imaging exam today in the US, with 70 million obtained each year in the ER, outpatient department, or as part of routine health assessments. This ‘6 in 1’ indication FDA clearance completes the entire qXR product suite of AI algorithms, covering the breadth of findings encountered on chest X-rays. Findings that can be categorized into six regions of interest are added including:

“There are more than 100 potential findings on a plain film chest X-ray that AI tools can help detect and assist radiologists with, supporting earlier recognition of abnormalities,” states Professor Amit Gupta, Division Chief of Cardiothoracic Imaging and Modality Director of Diagnostic Radiography at University Hospitals Cleveland Medical Center. “Tools such as qXR-Detect go beyond binary detection alone. In addition to flagging potential abnormalities, the system provides visual localization and explainability, such as through bounding boxes and region-of-interest labels, which helps the interpreting radiologist quickly understand where and why an alert has been generated. When used alongside standard clinical interpretation, chest radiography augmented with AI-based detection and localization can offer a practical frontline support tool for identifying findings such as lung nodules and other abnormalities that may warrant closer attention or further diagnostic workup.”

“These super six indications cleared by the FDA for qXR-Detect establish&nbsp;Qure.ai&nbsp;as the foremost commercial AI company, with the most comprehensive regulatory clearances for chest X-ray globally,” states Samir Shah, Chief Medical Officer at&nbsp;Qure.ai.&nbsp;“qXR-Detect is also the only chest X-ray CADe device cleared by the FDA with a Predetermined Change Control Plan (PCCP). This will help assure US health system customers access to the most up-to-date version of the algorithm as models and architecture evolves. This new clearance is testimony to the robust FDA regulatory process&nbsp;Qure.ai&nbsp;upholds and an exciting moment for all involved in the quest to create a stage shift in lung cancer.”

To achieve the FDA clearance, a performance test of qXR-Detect was conducted as a standalone and a multi-reader multi-case (MRMC) clinical study. The device showed good performance in both and met the predefined success criteria.

Qure.ai’s&nbsp;FDA cleared indications now total 26 across 9 products for X-ray and CT, exceeding 65 CE certified indications and other global validations. The latest FDA clearance adds breadth to the product portfolio in the US with the existing clearances for:

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Qure.ai nets six new indications cleared by the FDA, taking the chest X-ray crown in the radiology AI race 

At the India AI Impact Summit 2026, Qure.ai outlined how AI can be embedded within public health systems to support population-scale screening and disease surveillance. The discussion took place during the panel, “Public Health Powered by AI: RailTel’s Collaborative Model for AI-enabled Inclusive Healthcare for Bharat and Beyond,” which examined how AI can be implemented within national health programmes as part of routine service delivery. The session brought together senior public health leaders from government, global health institutions, academia, and industry to discuss how AI can be deployed at scale within national health systems.

The panellists included Sunil Kumar Barnwal, CEO, National Health Authority; Prof. Anubha Gupta, Professor, Indraprastha Institute of Information Technology, Delhi; Jean Philbert Nsengimana, Chief Digital Advisor, Africa Centres for Disease Control and Prevention (Africa CDC); and Ankit Modi, Chief Strategy &amp; Growth Officer, Qure.ai. The session was moderated by Shri K. Manohar Raja, Principal Executive Director, RailTel Corporation of India Limited.

“Public sector digital infrastructure plays a key role in helping proven and widely deployed health technologies scale at the population level,” said Shri K. Manohar Raja, Principal Executive Director, RailTel. “By providing reliable networks and systems, institutions like RailTel can support technology companies in expanding deployments across public programmes in India and beyond, helping reduce implementation friction.”

Emphasising the importance of national digital foundations, Sunil Kumar Barnwal, CEO of the National Health Authority, highlighted how India’s public digital health architecture enables AI adoption at scale. “Digital foundations like Ayushman Bharat Digital Mission are designed to support integrated care delivery across the country. When AI-enabled diagnostics are embedded within these systems, they can help shift healthcare from reactive treatment to proactive risk identification, enabling better monitoring and informed policymaking at a national level,” said Barnwal.

Speaking on the panel, Ankit Modi, Chief Strategy &amp; Growth Officer, Qure.ai, noted that the real challenge for health systems is not access to technology, but sustained deployment of it at scale. He pointed out that when AI is embedded into routine screening programmes, it enables continuous disease surveillance, early detection and structured population-scale screening. By generating real-time, population-level insights through integrated dashboards, AI systems support proactive identification of high-risk individuals. 

It is the first Indian AI company recommended by the World Health Organization for autonomous tuberculosis screening, reflecting its clinical rigour and relevance to public health systems. Qure’s AI tools are deployed within national disease surveillance programmes in countries including Malaysia, Thailand, El Salvador, and Colombia, and are used across diverse care settings ranging from rural primary health centres to tertiary hospitals.

“Our experience across large public health programmes shows that embedding AI into routine screening and diagnostic workflows delivers immense clinical value,” said Ankit Modi, Chief Strategy &amp; Growth Officer, Qure.ai. “It helps health systems manage workload more efficiently, even in settings with limited infrastructure. Deployments at India’s scale demonstrate how public health AI can be implemented reliably and adapted by other health systems across the world.”

The discussion underscored the importance of treating AI as part of public health infrastructure rather than a standalone tool. The session highlighted how collaboration between government institutions, public sector entities, and technology providers can enable AI to be implemented within regulatory frameworks and public programmes. It also reflected the growing readiness of Indian health systems to evaluate and adopt proven AI solutions in a structured and accountable manner.

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Qure.ai Demonstrates How India-Built AI Is Powering Public Health at Population Scale, with Global Relevance

~The findings draw on state-level implementations to assess how AI is moving beyond pilots into routine public healthcare~

New Delhi, India | 16 February 2026: Qure.ai today unveiled its latest report, ‘AI in Action: Transforming Health Outcomes Across India’s Care Spectrum’, at the India AI Impact Summit, outlining how artificial intelligence is being deployed at scale across India’s public healthcare system to address critical challenges such as tuberculosis, lung cancer, and acute neurological conditions.

The report consolidates real-world evidence from large public health programmes, state-wide deployments, and multi-country clinical studies, demonstrating how AI, when embedded into existing healthcare workflows, can accelerate diagnosis, reduce system-level delays, and improve access to timely care without adding cost or operational complexity for patients or providers.

Central to the report is the role of state-level partnerships in enabling AI adoption at population scale. Across Maharashtra, Karnataka, Goa, Punjab and other states, governments and public health agencies have integrated AI into routine imaging and emergency care pathways to strengthen detection, triage and follow-up. 

●	In Maharashtra, AI-enabled incidental screening across public and private facilities contributed to an estimated 35% increase in tuberculosis detection, including among asymptomatic patients undergoing X-rays for unrelated reasons. 

●	In Karnataka, a government-led partnership enabled the incidental detection of over 6,400 TB cases alongside high-risk lung nodules through a single AI-driven workflow. 

●	In Goa, a statewide public health deployment screened over one lakh routine chest X-rays, leading to 20 confirmed lung cancer diagnoses through structured referral pathways. 

●	In Punjab, a state-supported hub-and-spoke stroke network reduced diagnostic turnaround time by up to 85%, protecting the critical “golden hour” even in district hospitals.

Beyond routine care delivery, the report illustrates how AI is being applied to large-scale disease surveillance and national public health initiatives. During the Maha Kumbh Mela, one of the world’s largest mass gatherings, AI-powered chest X-ray analysis was deployed for rapid tuberculosis surveillance in a high-density, high-risk environment. The system flagged abnormalities in 36% of X-rays, enabling early identification and triage of presumptive TB cases and offering a replicable model for mass gatherings and outbreak-prone settings.

Speaking at the launch of the report, Ankit Modi, Founding Member and Chief Strategy &amp; Growth Officer, Qure.ai, said, “What this report shows is not just where AI has been deployed, but where public healthcare is headed. Through state partnerships, AI is moving from being an intervention to becoming part of the system itself, built into how screening, surveillance, and emergency care are delivered. As these models scale, AI has the potential to consistently shift detection earlier, reduce delays across care pathways, and make continuity of care the default rather than the exception, using infrastructure that already exists.”

In addition to on-ground implementation outcomes, the report draws on independent Health Technology Assessment (HTA) evaluations conducted under the Government of India, which validate AI-powered chest X-ray screening as both clinically effective and cost-saving for tuberculosis detection. The assessments show a reduction of approximately ₹10,000 per TB case detected compared to existing diagnostic pathways, reinforcing the case for AI as a scalable intervention that can strengthen public health programmes without increasing system costs.

Taken together, the evidence presented in AI in Action points to a clear shift in how India’s public healthcare system can evolve, by embedding AI as a foundational layer across screening, surveillance, care coordination, and emergency response. As state partnerships deepen and these models scale, AI has the potential to move healthcare delivery from reactive to proactive, enabling earlier intervention, more reliable follow-up, and stronger system-wide resilience across India’s care continuum.

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Qure.ai Unveils ‘AI in Action’ Report at India AI Impact Summit, Mapping AI’s Role Across India’s Public Healthcare System

Over 10,500 lung nodules flagged through AI review of routine chest X-rays, reducing time to diagnosis by over 50%

The Government of Goa today shared early outcomes from its AI-enabled lung cancer screening programme implemented across the state’s public healthcare system. The initiative integrates artificial intelligence-based chest X-ray analysis into routine clinical workflows at government health facilities, enabling earlier detection of lung abnormalities without requiring additional tests or patient visits.

Lung cancer is one of the leading causes of cancer-related mortality in India, primarily due to late-stage diagnosis. Goa’s programme addresses this challenge by automatically reviewing every chest X-ray conducted in public health facilities for early signs of lung abnormalities, even when the scan is performed for unrelated clinical indications. This approach allows clinicians to identify potential lung cancer cases earlier and initiate timely follow-up.

Speaking on the programme, Shri Vishwajit Rane, Hon’ble Health Minister of Goa, said, “The Department of Health has been consistently advancing initiatives focused on early detection, preventive healthcare, and cancer screening to strengthen the public healthcare system. By embedding AI into routine diagnostic processes, Goa is reinforcing early detection in a structured and scalable manner. This programme ensures that advanced technology supports clinical decision-making without adding cost or complexity for patients. Early diagnosis must be accessible to all, and should not be limited by geography or affordability. Integrating AI into public healthcare represents the way forward in delivering timely, efficient, and equitable care to our people.”

The programme has been implemented in close coordination with clinicians across Goa’s public health system. Pulmonologists and radiologists from government hospitals have guided the clinical adoption of AI-enabled triaging, ensuring alignment with existing diagnostic pathways and follow-up protocols.

Since deployment, the initiative has analyzed 1,06,248 chest X-rays across 18 public healthcare sites in the state. The AI system flagged 10,564 lung nodules, including 1,619 classified as high-risk, enabling clinicians to prioritize patients requiring urgent evaluation. To date, this has led to 18 confirmed lung cancer diagnoses and reduced the average time to diagnosis by more than 50%.

Ankit Modi, Founding Member and Chief Product Officer, Qure.ai, said, “What makes Goa’s programme significant is its ability to deliver impact at scale using infrastructure that already exists within the public healthcare system. By leveraging routine chest X-rays, the state has enabled earlier identification of lung abnormalities without introducing additional tests or burden on patients. The outcomes reinforce that clinically guided, system-integrated AI can accelerate diagnosis and support more timely care across public health systems.”

Praveen Rao Akkinepally, Country President and Managing Director, AstraZeneca India, said, “This is a significant milestone for the state of Goa. We are honoured to partner with the Department of Health Services, Goa, and Qure.ai, and congratulate the team on surpassing 100,000 AI-enabled lung screening scans. It underscores our shared purpose of earlier detection and equitable access to healthcare. With AstraZeneca’s science, Goa’s public health leadership, and Qure.ai’s capability, we are bringing technology closer to patients, lowering barriers to care, and building scalable, data-driven pathways across India, so people are identified sooner and connected to the right care at the right time.”.

The Government of Goa plans to further expand the programme by integrating AI-enabled screening into mobile health units and community outreach services, reinforcing its commitment to strengthening early diagnosis and improving cancer care outcomes across the state.

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 Goa Crosses 1 Lakh Chest X-Rays Reviewed Using AI in Public Health System, Identifies 18 Lung Cancer Cases

AI innovation will improve diagnostics of preventable infectious disease&nbsp;including TB &amp; pneumonia for global health progress

In an&nbsp;effort&nbsp;to&nbsp;advance health equity and reach the people that need help most, global digital health innovator&nbsp;<a href="https://ind01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.qure.ai%2F&amp;data=05%7C02%7Caditya.tiwari%40qure.ai%7Cc9dfe0c2a93248ec5e3108de598b99e4%7C429de9c6796848e99601d3bd6c6424bb%7C0%7C0%7C639046653272096759%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&amp;sdata=xRfg7NLeEeezoiXXreocjL%2BxwCXYoQe%2FT7KrtQ4ER9w%3D&amp;reserved=0" target="_blank">Qure.ai</a>&nbsp;has received a grant from&nbsp;the Gates Foundation.

The multimillion-dollar grant will allow&nbsp;Qure.ai to&nbsp;develop a&nbsp;large&nbsp;open-source multi-modal database to further advance future prevention and&nbsp;identification&nbsp;innovations. It will support WHO lung-health diagnostic pathways plus augment non-identifiable clinical history, medical images&nbsp;(Chest&nbsp;X-Ray,&nbsp;Thoracic&nbsp;Ultrasound,&nbsp;High&nbsp;Resolution&nbsp;CT), cough/lung recordings, and laboratory or biological markers to enable researchers and innovators around the world to develop, validate, and refine new AI models for the good of all.  &nbsp;

This grant will also allow&nbsp;Qure.ai&nbsp;to&nbsp;develop&nbsp;AI-enabled point-of-care ultrasound&nbsp;algorithms&nbsp;as a ‘tool’ for the early detection of TB and pneumonia, two of the world’s deadliest infectious diseases in under-resourced regions. Both are curable if caught early yet TB deaths are approximately 1.23 million annually, pneumonia 2 million each year, 700,000 of which are children under five.  &nbsp;

“In a bid to reach the unreachable we have innovated our way around the world over the last 10 years,&nbsp;taking AI-enabled X-ray to some of the remotest regions of sub-Saharan Africa, to the heights of Everest and depths of&nbsp;rural Southeast Asia, tackling the detection and diagnosis of TB. This is powerful progress that has reduced diagnosis rates from 14 days to 1-2 days, without even a clinician present. Now, with this grant from&nbsp;the Gates Foundation,&nbsp;we are excited to leverage this expertise further to scale and reach more people,” states Prashant Warier, Co-founder and CEO of&nbsp;Qure.ai. &nbsp;

“With the very latest developments in digital health and artificial intelligence,&nbsp;Qure.ai can help reach healthcare’s blind spots, bringing high-quality diagnostics within reach of every clinic, health worker, and child, no matter where they live,”&nbsp; adds Dr. Shibu&nbsp;Vijayan, Chief Medical Officer – Global Health at&nbsp;Qure.ai.   &nbsp;

“This grant will allow us to build on the years of continuous innovation we have spearheaded in public health and our commitment to pushing the boundaries of what AI can do for global health. It brings together pneumonia, tuberculosis, and broader lung health priorities, with a focus on children in low and middle-income countries. A child dies of pneumonia every 43 seconds which is an unacceptable and an avoidable loss. It underscores the urgent need for better diagnostics and equitable access to care,”&nbsp;said Dr&nbsp;Justy Antony Chiramal, Project Lead and Clinical Director, Global Health Innovation at&nbsp;Qure.ai. &nbsp;

Qure.ai&nbsp;is a global health innovator, with deployments across 105+ countries and 4,800+ sites worldwide identifying and managing TB, Lung Cancer and Neurocritical findings such as Stroke.  

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Qure.ai secures major global health grant to build AI-powered point-of-care ultrasound

End-to-end&nbsp;specialist&nbsp;AI to&nbsp;support high quality patient care&nbsp;&nbsp;

Horizon Health&nbsp;Network&nbsp;(Horizon), the operator of&nbsp;12 hospitals and more than 100 medical facilities and clinics across&nbsp;the&nbsp;province of&nbsp;New Brunswick&nbsp;in Canada,&nbsp;has&nbsp;entered into&nbsp;a partnership with global health innovator Qure.ai to evaluate and implement an end-to-end artificial intelligence (AI) lung cancer care suite.

This agreement&nbsp;supports Horizon's preparation for&nbsp;an anticipated&nbsp;province-wide low-dose CT lung cancer screening program for high-risk patients. The collaboration also enables proactive advancement in chest X-ray incidental lung cancer detection across a broader patient population.&nbsp;

Through this&nbsp;innovative&nbsp;partnership, Horizon is building the infrastructure, workflows, and clinical integration capabilities to be ready for coordinated provincial lung cancer screening initiatives.&nbsp;

Lung cancer is the leading cause of cancer death in&nbsp;North America, accounting for more cancer deaths than colon, breast, and prostate cancers combined.&nbsp;Early detection at stage I, rather than late stage III or IV,&nbsp;boosts survival rates and reduces the need for therapeutic or surgical intervention.&nbsp;&nbsp;

“This agreement&nbsp;with Qure.ai reflects our commitment to innovation and advancing patient care through rigorous evaluation of emerging technologies," states Zach Kilburn, Chief Digital Officer at Horizon Health Network. "The AI-powered software will integrate seamlessly with our existing&nbsp;infrastructure&nbsp;to support clinical confidence in decision-making and streamline patient management workflows. By building this infrastructure now,&nbsp;we're&nbsp;positioning our&nbsp;clinicians&nbsp;to support high-quality, coordinated lung cancer care across the health&nbsp;care ecosystem.”&nbsp;

“Proactive&nbsp;CT-based&nbsp;lung cancer&nbsp;screening&nbsp;strategies are&nbsp;a giant step forward, but&nbsp;only&nbsp;one part of the battle against&nbsp;lung&nbsp;cancer.&nbsp;AI has the power to cast&nbsp;a wider&nbsp;net, to&nbsp;identify&nbsp;small lung nodules that can be indicative of&nbsp;early-stage&nbsp;lung cancer on routine&nbsp;CT and&nbsp;X-rays that may be&nbsp;obtained&nbsp;for other&nbsp;indications. This can include pre-operative examinations or&nbsp;trauma related&nbsp;admissions,”&nbsp;states&nbsp;Jim Mercadante, Chief Commercial Officer&nbsp;at Qure.ai. “We are delighted to be entering into a progressive&nbsp;lung cancer&nbsp;AI partnership with Horizon Health Network&nbsp;in Canada&nbsp;and supporting them with digital transformation.”&nbsp;&nbsp;

Qure.ai is a global leader in healthcare AI and digital health boasting deployments&nbsp;in over 107&nbsp;countries across&nbsp;5200+ sites.&nbsp;The Qure.ai lung cancer solutions&nbsp;have class III medical device license approval from Health Canada&nbsp;and FDA clearance in the USA. They&nbsp;can be deployed as individual products, or collectively as a suite for a unified and cohesive workflow.&nbsp;qXR-LN&nbsp;powers the incidental detection of lung nodules on chest X-ray;&nbsp;qCT-Quant&nbsp;assesses&nbsp;and&nbsp;quantifies&nbsp;lung nodules&nbsp;on CT&nbsp;scans; and&nbsp;qTrack&nbsp;coordinates patient management to support lung nodule clinics or nurse navigators.&nbsp;&nbsp;&nbsp;

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Horizon Health Network and Qure.ai partner to advance province-wide early lung cancer detection in Canada 

Catharina Ziekenhuis &amp; UMC Utrecht go-live with Qure.ai&nbsp;&nbsp;

Two major Dutch hospitals, Catharina Ziekenhuis in Eindhoven and University Medical Center (UMC) Utrecht, are integrating artificial intelligence (AI) from <a href="https://www.qure.ai/" target="_blank">Qure.ai</a> into chest X-ray workflows to support earlier and more consistent detection of potentially cancerous lung nodules.&nbsp;

The hospitals are striding ahead by progressively adopting AI-enabled lung nodule programs to establish opportunistic screening pathways that can lead to earlier detection of lung cancer and reduce variation in referral decisions across experience levels. Qure.ai’s chest X-ray solution, qXR, strengthens this effort by flagging subtle nodules helping the radiologists with the detection of nodules, even when patients are scanned for unrelated reasons.&nbsp;

UMC Utrecht, one of the Netherlands’ foremost university hospitals, brings both academic and clinical weight to the initiative. UMC Utrecht is at the forefront of using AI in its radiology clinic and has a strong scientific track record in the radiological aspects of lung cancer and AI. As an academic hospital with a strong teaching mandate, it serves a broad patient base while also preparing future clinicians to work confidently with AI-enabled diagnostics.&nbsp;

&nbsp;“AI-enabled diagnostics in radiology are an important tool for today's radiology practice,” states Dr. Firdaus Mohamed Hoesein, Thoracic Radiologist and AI-expert at UMC Utrecht. “By integrating this AI program into our workflow, we can significantly enhance our ability to detect subtle lung nodules, which is paramount for the early diagnosis of lung cancer. This initiative directly aligns with our mission to find lung cancer at earlier stages and improve patient outcomes.”&nbsp;

Dr Joost Nederend, Radiologist at Catharina Ziekenhuis adds, “There is growing evidence that AI can improve detection rates without compromising - and potentially even improving - the positive predictive value for referrals. It can also be valuable in supporting consistent decision-making, especially when chest X-rays are interpreted by radiologists from different subspecialties, those in the earlier stages of their careers, or residents in training.”&nbsp;

Catharina Ziekenhuis is a public tertiary care hospital with advanced capabilities to treat lung cancer. A large share of chest X-rays originates from general practitioner referrals for symptoms like persistent cough or other concerns.&nbsp;&nbsp;

Earlier this year, Erasmus Medical Centre, one of the largest and most authoritative scientific university medical centres in Europe, located in Rotterdam, extended its long-term collaboration with Qure.ai by commencing an innovative Chest X-ray AI study.&nbsp;&nbsp;

&nbsp;&nbsp;Bhargava Reddy, Chief Business Officer, Oncology at Qure.ai states, “Lung cancer remains the leading cause of cancer-related deaths worldwide, including in the Netherlands. To fight back, we need to shift the focus to early detection. Specialist healthcare AI can accelerate this transformation by acting as a tireless second set of eyes, spotting small lung nodules on X-rays that might otherwise be missed. At the same time, it builds knowledge and know-how that drive clinical, operational, and economic value within hospitals and across health systems.”

He continues, “The momentum in the Netherlands is unmistakable. From Erasmus Medical Centre to Catharina Ziekenhuis and UMC Utrecht. Institutions are confidently deploying AI that both elevates clinical standards and aims to future-proof Dutch healthcare.”&nbsp;

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Momentum builds in the Netherlands for AI-driven early lung cancer detection 

New evidence presented at ESMO AI conference highlights how AI can be a&nbsp;silent accelerator within diagnostic pathways&nbsp;&nbsp;

A new study presented at the European Society for Medical Oncology (ESMO) AI Congress&nbsp;demonstrates&nbsp;how AI&nbsp;can help&nbsp;identify&nbsp;patients&nbsp;passively&nbsp;at risk of&nbsp;early-stage&nbsp;lung cancer&nbsp;coming to different&nbsp;departments,&nbsp;long before traditional pathways might flag a concern.&nbsp;

Lung cancer&nbsp;remains&nbsp;the leading cause of cancer deaths&nbsp;In Europe. While proactive low-dose CT screening for lung cancer is&nbsp;established&nbsp;in some countries, it is not globally standard. This research provides compelling evidence that AI-assisted chest X-rays&nbsp;detection&nbsp;could bridge the gap, turning every hospital radiology department into a potential early detection point&nbsp;The main advantage is its passive nature and the fact that the&nbsp;huge volumes of&nbsp;Chest&nbsp;X-rays&nbsp;of the&nbsp;patients coming to different departments can be&nbsp;.passively looked for risk of Lung Cancer&nbsp;and can be flagged..&nbsp;

The study analysed over 30,000 chest X-rays taken for a wide range of clinical indications. Using&nbsp;Qure.ai’s&nbsp;AI-powered algorithm for chest x-ray interpretation, 71 individuals were flagged as high-risk for malignancy. Follow-up CT scans and biopsies confirmed five lung cancer cases, ranging from early to advanced stages. One case was detected at&nbsp;a very early&nbsp;stage (Stage IA3), allowing&nbsp;timely&nbsp;treatment&nbsp;of the patient which could have been missed if AI&nbsp;was&nbsp;not used&nbsp;

“These findings illustrate how AI can act as a silent accelerator within the diagnostic pathway,” said&nbsp;Dr. Rahul Ravind, Medical Oncologist, Renai&nbsp;Medicity,&nbsp;Kochi&nbsp;and lead investigator. “By embedding AI into everyday hospital workflows, clinicians can catch potential cancers much earlier, even when tests were ordered for non-oncological reasons. AI can help extend the benefits of early diagnosis beyond formal screening programs, making it possible even in hospitals that may not have dedicated lung cancer pathways or CT-based screening access.”&nbsp;

“We’re&nbsp;seeing AI bridge one of healthcare’s biggest gaps – the time between the first test and the right diagnosis. That acceleration can completely change outcomes for patients. This study underscores AI’s potential to transform opportunistic screening using chest X-rays that are already part of routine care. By alerting clinicians to suspicious findings in real time, AI can shorten diagnostic timelines and enable faster&nbsp;referral,&nbsp;improving chances of&nbsp;early treatment,” says&nbsp;Sagar Sen, VP, life sciences, Qure.ai&nbsp;&nbsp;

The findings are based on real-world data from Renai&nbsp;Medicity, a tertiary care hospital in Kochi, India, collected between March 2024 and July 2025.&nbsp;

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AI cuts diagnostic delays in lung cancer detection, offering a blueprint for faster, smarter hospital care 

Yashoda Hospital, Hitech City, in collaboration with Qure.ai and AstraZeneca, has launched an AI-enabled Lung Nodule Clinic to support earlier identification and timely management of lung cancer and other pulmonary diseases.

Lung cancer is one of the leading causes of cancer-related deaths in India¹. Most patients are diagnosed at an advanced stage because early disease often has no symptoms and is easily missed on routine imaging². A large proportion of cases in India present late, which limits the chances of curative treatment². India does not have a national lung cancer screening program for high-risk individuals³, which makes structured imaging pathways an important way to support earlier detection. 

Pulmonary nodules are often subtle findings that can vary in size, density, and location, which makes them challenging to identify consistently on routine chest imaging. The new Lung Nodule Clinic at Yashoda Hospital, Hitech City, integrates Qure.ai’s AI solutions into chest X-ray workflows to flag, risk assess, and track these findings in a structured manner. Nodules can be indicators of early lung cancer or other conditions such as tuberculosis, sarcoidosis, or lymphoma. The AI-supported pathway helps clinicians prioritise higher-risk cases and ensure timely and consistent follow-up.

“This program shows how AI can be integrated into clinical workflows to support earlier identification and structured management of lung disease,” said Dr. V. Nagarjuna Maturu, Head of Department, Pulmonology, Yashoda Hospital, Hitech City. “The pathway ensures that incidental findings are consistently tracked and followed up. Embedding AI into routine workflows has helped Yashoda Hospital create a scalable model for proactive lung health. This shows how coordinated use of data and clinical expertise can improve real-world diagnosis and outcomes.”

A nurse navigator model supports the system and helps patients move from AI flagging to counselling, review, and next steps. “Standardised workflows help avoid delays and ensure consistent communication and documentation,” added Dr. Vipul Garg, lead Consultant, Yashoda Hospitals Nodule Clinic.

Since deployment, more than 17,000 chest X-rays have been analysed using Qure.ai’s AI. The program has identified over 960 nodules. Of these, 136 were classified as high risk and 77 patients were sent for expedited CT scans and pulmonology review. Confirmed diagnoses include lung cancers as well as other significant lung diseases, highlighting the broader value of this pathway for proactive lung health. 

“AI is becoming an important part of how health systems strengthen early diagnosis and reduce the burden of late stage lung disease,” said Sagar Sen, Vice President, Life Sciences, Qure.ai. “By integrating intelligence into routine imaging, hospitals can turn everyday X-rays into an opportunity for earlier detection and more coordinated care. The Lung Nodule Clinic at Yashoda Hospital is a strong example of how technology and clinical expertise can work together to create a more proactive approach to lung health.”

The AI supported pathway represents an important move toward structured, data driven lung health and demonstrates the role of modern diagnostic tools in improving early detection in high volume hospital settings.

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