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Erasmus MC extends its collaboration with Qure.ai

qTrack

As we reflect on the past year, I am filled with appreciation for your trust and collaboration that have propelled our mission further at Qure. We are united in our commitment to use artificial intelligence to make healthcare accessible, equitable, and timely, aiming to transform a billion lives.

To date, we have achieved a pivotal milestone by positively impacting over 20 million lives through our advanced AI-driven screening solutions in X-rays and CTs across nearly 2,700 healthcare facilities in over 90 countries. Each number represents a personal story of hope and health, enhanced by our collective efforts.

Over the past year, we helped screen over 1 million patients for Tuberculosis in 24 African countries, deploying our technology in some of the most remote areas without internet or electricity. Internationally, our solutions have assisted physicians in alerting more than 270,000 individuals to early signs of Tuberculosis. This global effort not only highlighted our technology’s reach but also our deep-rooted commitment to making a difference where it’s needed most.

This year also marked several groundbreaking achievements that further established our leadership in AI healthcare. We published pioneering research on incidentally detecting heart failure through ChestX-Ray AI, a significant step forward in cardiac care. Our work in lung cancer was also recognized in the prestigious journal Nature as one of the year’s most critical medical studies. Additionally, we received three more FDA approvals, enabling broader clinical use of our solutions in the U.S.

Our solution’s potential was showcased in discussions with global leaders like Indian Prime Minister Shri Narendra Modi and internationally known philanthropist Bill Gates. We also hosted our first user group meeting focused on AI’s role in combating Tuberculosis, enhancing global collaboration against this disease.

Our partnerships with the NHS and AstraZeneca have been instrumental, impacting a million and two million lives respectively through AI-driven early detection in diverse health scenarios. Moreover, our technology alerted 100,000+ neurocritical patients to signs of stroke, potentially saving lives by enabling timely intervention and reducing emergency response time by approximately 6 hours per patient undergoing mechanical thrombectomy.

As we step into another year filled with new challenges and opportunities, I carry a profound sense of responsibility and a renewed commitment to our mission. Your continued support has been the backbone of our innovation and impact.

Thank you for being an integral part of our transformative journey. Together, we are not just imagining a healthier future; we are actively shaping it, one life at a time.

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Qure.ai FY 23-24 Impact Report: Global AI Healthcare Innovations

The "X-rays on Wheels" case study by STDC Nagpur focuses on a TB screening initiative targeting tribal communities in Maharashtra, who have a significantly higher TB prevalence than the national average.

In December 2019, STDC introduced a mobile medical van equipped with an X-ray machine to reach remote tribal areas. However, delays in diagnosis and treatment occurred due to the absence of on-site radiologists, extending the turnaround time for sputum collection to over 1.5 months. To address this, STDC Nagpur partnered with Qure.ai in January 2023, integrating qXR, the AI-powered chest X-ray screening solution,  which identified presumptive or abnormal cases from X-rays in real-time. This significantly reduced the turnaround time from 1.5 months to one week.

During the project, over 6,500 X-rays were conducted across 16 districts, with 730 cases flagged as abnormal and 728 individuals marked as TB presumptive. The collaboration not only expedited TB detection but also helped identify other chest abnormalities, enhancing overall healthcare in these vulnerable communities. This partnership between STDC and Qure.ai has transformed the screening process, improving efficiency and outcomes for TB management in tribal regions.

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Qure.ai’s AI Transforms TB Screening in Tribal Communities

Qure.ai, in collaboration with Health Through Walls (HtW), has implemented an AI-powered TB screening solution in prisons across Haiti, the Central African Republic (CAR), and Mozambique. This initiative addresses the critical health challenges faced in overcrowded and resource-limited correctional facilities, where TB is a major risk due to poor sanitation and ventilation.

Traditionally, TB screenings in these prisons relied on radiologists located remotely, causing significant delays. Qure’s AI solution - qXR - has transformed the screening process by enabling rapid interpretation of chest X-rays. In 2022, over 5,000 inmates were screened in five Haitian prisons. Of these, 852 individuals were flagged for abnormal lung findings by the AI system, with 544 confirmed TB cases following microbiological testing.

The AI-powered solution greatly reduced the diagnosis time from one week to less than a minute, facilitating faster isolation and treatment, thus reducing the spread of TB within prisons and surrounding communities. The qXR tool, CE MDR Class IIb certified and WHO-evaluated, detects multiple lung abnormalities, including TB and lung cancer, ensuring comprehensive lung health screening.

This partnership between Qure and HtW demonstrates the potential of AI to revolutionise TB eradication efforts, especially in vulnerable populations. By providing timely TB detection in prisons, Qure’s AI solution is helping to save lives and improve public health in regions with limited access to radiologists.

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Healthcare Screening in Prisons with AI

South Africa faces a severe TB crisis, with 280,000 cases and 54,000 deaths annually. The situation is complicated by high HIV prevalence, limited healthcare access, and medical personnel shortages. Factors such as poverty, inequality, malnutrition, smoking, and silicosis contribute to the high TB prevalence.&nbsp;

The AI-Assisted TB Screening Collaboration&nbsp;

The KwaZulu-Natal Department of Health collaborated with USAID, THINK, LTE Medical Solutions, and Qure.ai to enhance TB diagnosis using AI-augmented portable X-ray machines in mobile vans. The program screened 6,500 individuals in its first six months, identifying 187 TB cases that might have been missed. AI offers faster turnaround times, higher accuracy, and the ability to diagnose TB without radiologists.&nbsp;

Benefits of AI in TB Diagnosis&nbsp;

Digital X-ray augmented by AI allows for timely diagnosis and treatment initiation, particularly in rural areas and for HIV-positive patients. Community outreach events encourage TB screening, and AI-assisted X-rays identify asymptomatic patients in hotspot areas. Health officials are optimistic about scaling the program and expanding its use to diagnose other diseases.&nbsp;&nbsp;

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How AI is Turning the Tide Against Tuberculosis in South Africa

Medica Group, the UK's leading provider of teleradiology services, has established a long-term strategic partnership with Qure.ai, a global leader in artificial intelligence-driven healthcare solutions. This collaboration is aimed at significantly improving the efficiency of NHS radiology scan workflows, which have been under considerable strain in recent years. Since 2020, Medica and Qure.ai have deployed the AI-powered decision support tool, qER, specifically designed for CT head scan examinations. This innovative technology has been instrumental in prioritizing critical cases, helping clinicians make faster and more accurate decisions, particularly in neuro-critical scenarios.

In their joint efforts, Medica and Qure.ai have released a new white paper that delves deeply into the evolution of AI within the radiology industry. This document sheds light on how AI is reshaping medical imaging, with particular emphasis on neuro-critical workflows. One of the key findings highlighted in the white paper is the remarkable accuracy of the qER tool, which demonstrated 93% accuracy in detecting intracranial hemorrhages (ICH) during a post-market surveillance study. This achievement underscores the transformative potential of AI in not only improving diagnostic accuracy but also enhancing patient outcomes by ensuring faster identification of life-threatening conditions.

The white paper offers an in-depth look at the reliability and integration of AI into teleradiology services, providing valuable insights into how AI-assisted workflows are revolutionizing the management of acute neurological conditions. By leveraging AI technology, clinicians can now navigate complex cases with greater precision, reducing diagnostic errors and expediting urgent treatment decisions. 

To explore these insights and understand how AI is shaping the future of radiology, fill out the form below to access the full white paper. Discover how this partnership between Medica and Qure.ai is transforming the landscape of teleradiology and improving the quality of patient care.

Fill the form to download the whitepaper now

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Data Driven Insights: The Role of AI in Radiology's Evolution

AI biases can emerge if algorithms are not validated on diverse populations.

qER, Qure.ai's AI solution for head CTs, has been rigorously evaluated using real-world, multi-regional data. As a result, qER reliably delivers excellent outcomes as a fully operational product for diverse populations globally. It has been extensively tested, deployed, and proven accurate across diverse patient demographics and scanning equipment, instilling true confidence in qER's reliability anywhere.

Qure's FDA-cleared qER software has gained traction in North America for its ability to swiftly and accurately triage, detect, and quantify pathology on head CTs. Covering four critical markers - hemorrhage, mass effect, midline shift, and fractures - qER delivers comprehensive insights to prioritize critical cases.

Monitoring severity over time aids in the long-term management of conditions such as hemorrhagic stroke and hydrocephalus. Input from North American hospitals and teleradiology groups guided qER's emphasis on essential CT measurements for emergency triage.

Additionally, qER-Quant leverages intelligent algorithms to precisely quantify volumes of intracranial structures and lesions. By determining the severity and progression of conditions like hemorrhagic stroke and hydrocephalus, qER-Quant further augments diagnostic and treatment decisions.

A study reviewed by vRad validated the qER algorithm against radiologist findings on more than 300,000 head CT scans. In one of the largest* evaluations conducted, qER delivered an outstanding AUC of 0.96, showcasing its ability to reduce door-to-scan interpretation times by up to 96% and accelerate communication of critical results to stroke teams within 5 minutes.

A noteworthy study published in The Lancet demonstrates a crucial validation of deep learning's capabilities in detecting urgent abnormalities on CT scans, using a diverse 300k scan dataset sourced from 20 centers in India. Key findings demonstrate exceptional diagnostic accuracy, with AUC values of 0.92 for detecting intracranial hemorrhage and over 0.90 for other specific bleed types.

Aarthi Scans and Labs, one of India's largest diagnostic chains, has adopted AI to enhance their teleradiology reporting - including for remote Tier 3 cities lacking nighttime radiologist coverage. This enables faster diagnosis and treatment for time-sensitive trauma cases. One deployment at Aarthi's Tenkasi center showed great insight into AI's clinical impact.

In Tenkasi, patients with conditions like stroke or traumatic brain injury used to wait over 7 hours

from the onset of symptoms to receive treatment due to delays in scan analysis, transfer to tertiary hospitals, etc.

According to Dr. Arunkumar Govindarajan, Aarthi's Director, "qER reduced symptom-to-treatment time by 30-70%, allowing more patients to be managed locally. By getting AI's assistance for faster diagnosis 24/7, cities like this could revolutionize outcomes for time-sensitive neurological injuries and disease."

A study detailed in Diagnostic Neuroradiology further cements the value of qER, focusing on the crucial aspect of intracerebral hemorrhage (ICH) management—hematoma volume quantification. Hematoma volume is a pivotal predictor of patient outcomes post-ICH, and the study aimed to validate a novel, fully automated software developed by Qure.ai for this purpose.

The study analyzed a significant patient population from the Swedish Stroke Register, including all patients diagnosed with intracerebral hemorrhage (ICH) in Region Skåne from 2016 to 2019. It compared ICH volume measurements from qER–NCCT, Qure.ai's automated quantification tool, against traditional methods like ABC/2 and manual segmentation using Sectra's software.

The results demonstrate qER–NCCT's ability to identify ICH with 97% sensitivity, proving highly efficacious in detecting bleeding. Volume measurements also showed excellent concordance between qER–NCCT and manual segmentation, considered the gold standard, with an interclass correlation of 0.96.

qER has gained widespread recognition and adoption within the United Kingdom's National Health Service (NHS) for its ability to expedite the identification of critical markers on head CT scans. Implemented in over 20 NHS trusts and health boards spanning England, Scotland, and Wales, qER processes over 1 million emergency scans every year, demonstrating high accuracy and reliability.

qER achieves exceptional AUC scores above 0.95 for the detection of intracranial hemorrhage and other hemorrhages. The deep learning algorithms also showcase near-perfect correlation with specialized neuroradiologist reporting for hematoma volume quantification, with an interclass correlation coefficient of 0.96.

Moreover, Medica, a leading teleradiology provider in the UK, has integrated Qure.ai's qER solution into its acute imaging workflow. qER serves as an "augmented intelligence" tool that analyzes non-contrast CT scans of the brain, flagging potential abnormalities and allowing for priority reporting based on clinical urgency.

As Dr. Garry Pettet, Consultant Radiologist, explains: "The qER algorithm is handy to reporting clinicians when interpreting acute brain CTs. It not only facilitates the rapid allocation of critically abnormal scans to our reporters but also helps to increase our reports' accuracy by lowering human error."

Recognizing the immense potential to augment emergency care pathways, the NHS selected qER as one of the inaugural winners of the prestigious Artificial Intelligence in Health and Care Award. The £140 million award spans 4 years to assess promising AI innovations in various clinical settings thoroughly. For qER, the aim is to widely implement it in Accident and Emergency (A&amp;E) departments to enhance diagnostic turnaround times for critical conditions like hemorrhagic strokes, ischemic strokes, and traumatic brain injuries.

The extensive piloting of qER technology within the NHS reflects an understanding of the pivotal role AI can play in bolstering overburdened care teams. With A&amp;E departments experiencing surging footfalls and exponential growth in required imaging, advanced analytics offered by solutions like qER could help alleviate clinical workload while boosting diagnostic precision.

Integrating AI-driven measurements into clinical practice could revolutionize diagnosing and monitoring neurologic and craniofacial conditions. It would provide a standardized reference supporting more informed decision-making and follow-up. Furthermore, initiatives like the AI-Based Stroke Care Network launched by Zydus Hospitals and Medtronic in Gujarat, India, aim to bridge significant gaps in stroke care, particularly in regions with limited access to specialized healthcare facilities, by leveraging AI to interpret CT scans remotely. Such innovations are pivotal in enhancing the timeliness and efficacy of stroke treatment, thereby improving survivability and reducing the incidence of long-term disability.&nbsp;

qER's seamless integration into healthcare systems across continents has accelerated the detection of neurologic emergencies, notably reducing response times and facilitating timely interventions. Through ongoing innovation and partnerships, algorithms like qER stand poised to radically improve healthcare delivery, offering tailored, efficient, and equitable medical solutions on a global scale.&nbsp;

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Qure.ai's qER: The Globally Proven Algorithm for Head CTs

Medica Group, a leader in UK teleradiology services, has partnered with Qure.ai, a globally recognized AI innovator in radiology, to integrate artificial intelligence into radiology workflows. This collaboration aims to enhance efficiency and prioritization within Medica’s radiology services, focusing on two impactful areas: improving CT head scan triage and refining study allocation processes.

One of the primary outcomes of this partnership will be an AI-driven decision support tool for CT head scans. This tool is designed to identify urgent cases quickly, allowing them to be flagged and prioritized based on clinical need rather than order of arrival. By doing so, Medica’s radiology teams can respond to high-priority cases more swiftly, integrating AI-identified critical findings directly into their diagnoses. This tool will initially support Medica’s NightHawk service, an out-of-hours radiology offering designed for urgent cases, and promises to streamline the process for rapid, effective clinical decision-making.

The second focus of the partnership is a bespoke AI-based workflow tool aimed at optimizing study allocation for Medica’s large network of over 435 radiologists. With this tool, Medica can handle its extensive workload more efficiently, automatically directing studies from NHS clients to the appropriate reporting teams. This kind of automation ensures smoother workflow management and allows radiologists to focus on interpreting images rather than on administrative processes.

Medica CEO Stuart Quin emphasized the company's ongoing commitment to adopting AI solutions that improve radiology efficiency and support clinical decision-making, seeing Qure.ai as an ideal partner due to its proven success in similar teleradiology applications. Qure.ai’s CEO, Prashant Warier, expressed enthusiasm for collaborating with Medica to bring AI’s potential to the forefront of the UK’s radiology market, highlighting the opportunity to support Medica’s expert radiologists in delivering high-quality care.

Through this partnership, Medica and Qure.ai are set to redefine teleradiology workflows, combining AI technology with expert radiological insights to advance patient care in the UK.

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24/7 emergency teleradiology reporting of stroke and neurocritical concerns

The Qure.AI Impact Report for FY 22-23 showcases the company's remarkable achievements in harnessing the power of artificial intelligence (AI) to revolutionize healthcare delivery worldwide. With a strong focus on enhancing accessibility, affordability, and timeliness of care, Qure.AI has made significant strides in transforming the healthcare landscape across diverse global settings.

The report presents a comprehensive overview of Qure.AI's impact through various case studies that highlight the company's innovative AI solutions. In Africa, Qure.AI has played a pivotal role in tuberculosis (TB) screening, leveraging their AI algorithms to detect TB cases accurately and efficiently. By enabling early detection and prompt treatment initiation, Qure.AI has contributed to reducing the burden of TB in the region, ultimately saving lives and improving public health outcomes.

In Vietnam, Qure.AI's AI-powered lung cancer detection system has demonstrated remarkable success. By analyzing medical images and identifying potential lung cancer cases, the company has facilitated early intervention and improved survival rates. This case study underscores the potential of AI in tackling critical health challenges and advancing cancer care in resource-constrained settings.

The report also sheds light on Qure.AI's impact in developed countries, such as the United States. The company's AI solutions for stroke care have shown promising results in optimizing treatment protocols and improving patient outcomes. By providing rapid and accurate assessment of stroke cases, Qure.AI has empowered healthcare providers to make timely decisions and deliver targeted interventions, ultimately reducing the devastating consequences of stroke.

In addition to these impactful case studies, the Qure.AI Impact Report highlights the company's strategic partnerships and collaborations with leading healthcare institutions, government agencies, and industry stakeholders. These partnerships have been instrumental in expanding the reach and impact of Qure.AI's AI solutions, fostering knowledge exchange, and driving innovation in the healthcare sector.

The report also showcases Qure.AI's impressive growth in AI deployment, with their solutions being adopted by an increasing number of healthcare facilities worldwide. This expansion demonstrates the growing recognition of the value and effectiveness of AI in healthcare and the trust placed in Qure.AI's cutting-edge technology.

Moreover, the report emphasizes Qure.AI's commitment to regulatory compliance and quality assurance. The company has achieved significant regulatory milestones, ensuring that their AI solutions meet the highest standards of safety, reliability, and efficacy. These achievements underscore Qure.AI's dedication to developing responsible and trustworthy AI technologies that prioritize patient well-being.

Looking ahead, the Qure.AI Impact Report outlines the company's future goals and aspirations. With a steadfast commitment to advancing AI innovation in healthcare, Qure.AI aims to further expand its global footprint, develop new AI applications, and continue collaborating with stakeholders to address pressing healthcare challenges. The company's vision is to democratize access to high-quality healthcare through AI, making a lasting impact on communities worldwide.

The Qure.AI Impact Report for FY 22-23 serves as a testament to the company's unwavering dedication to leveraging AI for the betterment of healthcare. Through their innovative solutions, impactful case studies, strategic partnerships, and regulatory achievements, Qure.AI has established itself as a leader in the field of AI-driven healthcare transformation. As the company continues to push the boundaries of what is possible with AI, it holds immense promise for revolutionizing healthcare delivery and improving the lives of millions across the globe.

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Qure.AI FY 22-23 Impact Report: Global AI Healthcare Innovations

In the heart of Uttar Pradesh's Bundelkhand region, Harriet Benson Memorial Hospital has been a cornerstone of healthcare since 1940. Specializing in maternal and child health, this 40-bed facility has continuously adapted to meet the evolving needs of its community. Recently, the hospital faced a significant challenge in diagnosing and managing tuberculosis (TB) effectively, leading to an innovative collaboration that's changing the landscape of TB detection.

Enter Qure.ai, a pioneering AI company that received a grant from the India Health Fund (IHF) to revolutionize TB diagnosis. Their solution? A point-of-care, smartphone-based chest X-ray tuberculosis triage system for both analog and digital X-rays. This groundbreaking technology allows for instant screening of chest X-ray films via smartphone photographs, marking a significant leap in diagnostic capabilities.

Harriet Benson Hospital integrated Qure's qXR + qTrack system, providing AI-powered pre-read assistance for TB detection. The impact was immediate and profound. The qTrack system delivered AI analysis results within a minute to technicians' smartphones, significantly accelerating TB diagnosis and treatment initiation.

The integration of this AI solution into the hospital's existing workflow was seamless, enhancing diagnostic procedures without disrupting established protocols. This allowed clinicians to maintain their focus on patient care while benefiting from AI efficiency. The results speak for themselves: diagnosis timelines were reduced from days to minutes, leading to quicker treatment commencement and improved patient outcomes.

The technology proved particularly valuable during the COVID-19 pandemic, facilitating efficient diagnosis amidst a surge in cases and limited medical practitioners. The hospital's regular caseload of 3 to 4 TB cases per week saw expedited diagnosis and intervention, ultimately benefiting patients.

By March 28, 2023, the partnership's impact was clear: out of 300 patients screened, Qure's AI solution identified 46 as potential TB cases. Subsequent tests confirmed 12 diagnoses, with these patients promptly beginning Anti-Tuberculosis Treatment (ATT).

This collaboration between Harriet Benson Memorial Hospital and Qure.ai sets a new standard for TB management and care. It demonstrates the transformative potential of AI in healthcare, especially in resource-constrained settings. The success of this partnership paves the way for wider adoption of AI solutions in healthcare, promising improved patient care even in the face of global health challenges.

As we look to the future of healthcare, the story of Harriet Benson Hospital and Qure.ai serves as a powerful example of how innovation and collaboration can drive meaningful change. To learn more about this groundbreaking initiative and its far-reaching impact, download the study below to read more.

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Qure.ai & Harriet Benson: AI-Powered TB Care Transformation

AI presents a significant opportunity to enhance the use of Chest X-rays (CXRs), particularly for active case finding for tuberculosis. While adoption is growing, especially in developing nations, it's still in its early stages and heavily dependent on donor funding.

This proposed AI CXR Index aims to guide stakeholders in prioritising and promoting adoption tailored to each country's needs. Analysis reveals key drivers, including the extent of need, intent, and ability to roll out AI. Recommendations are provided for stakeholders to facilitate adoption and effectiveness.

Through comprehensive analysis, four key dimensions driving the use of AI for CXRs have been identified: the extent of need, level of awareness, intent, and interest, and the ability to roll out AI technology. These dimensions encompass various factors, such as the shortage of radiologists, awareness among decision-makers, infrastructure availability, and regulatory frameworks.

Countries were further categorised into five archetypes based on their scores, ranging from Frontrunners ready for scale to Skeptics with the ability but lacking intent. This classification facilitates tailored support from stakeholders to each group of countries.

Lastly, several recommendations have been articulated for key stakeholders, including AI and hardware companies, donors, multilaterals, and high TB-burden countries, aimed at fostering greater adoption and effectiveness of AI for CXRs.

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AI Adoption for X-rays : A roadmap for future

In the heart of southern Africa, nestled within the rugged mountains of Lesotho, a quiet revolution is unfolding in the realm of healthcare. This transformation is spearheaded by an extraordinary collaboration between Partners In Health (PIH), the Ministry of Health of Lesotho, and Qure.ai, a trailblazer in artificial intelligence (AI) solutions for healthcare. United by a shared vision to combat tuberculosis (TB) and elevate healthcare standards nationwide, this partnership is a beacon of hope for a nation grappling with a high disease burden amidst limited resources.

Lesotho, a kingdom steeped in natural beauty and cultural richness, has long been confronted with formidable healthcare challenges. The high prevalence of TB, compounded by a scarcity of medical professionals and infrastructure, has cast a shadow over the lives of countless individuals and communities. However, the unwavering dedication of PIH and its partners has ignited a spark of change, illuminating a path towards a brighter, healthier future.

At the forefront of this transformative journey, PIH has embraced the power of innovation to address Lesotho's critical healthcare needs head-on. By implementing comprehensive programs focused on the national diagnosis, treatment, and supportive care for multi-drug-resistant tuberculosis (MDR-TB), PIH is revolutionizing the landscape of TB care in the country. These initiatives are not merely stopgap measures; they represent a fundamental shift in ensuring access to life-saving services for the most vulnerable populations, those who have long been left behind by traditional healthcare systems.

The cornerstone of this healthcare revolution lies in the groundbreaking partnership with Qure.ai, a visionary in the field of AI-powered healthcare solutions. Qure.ai's cutting-edge qXR algorithm has emerged as a game-changer in the fight against TB, enabling early detection and rapid intervention. By harnessing the power of AI, this technology has become the backbone of community screening programs across seven crucial locations in Lesotho: Bobete, Nkau, Nohana, Tlhanyaku, Lebakeng, Mafeteng, and Qacha's Nek.

The impact of the qXR algorithm since its implementation in July 2022 is nothing short of remarkable. With over 6,000 scans processed, the AI-powered system has identified approximately 1,100 individuals with potential TB cases, paving the way for further confirmatory testing against the gold standard – GeneXpert. This achievement is a testament to the transformative potential of leveraging technology in healthcare, offering a glimmer of hope for a TB-free future in Lesotho.

But the significance of this healthcare revolution extends far beyond the realm of statistics and algorithms. It is a story of resilience, of communities coming together to overcome seemingly insurmountable odds. It is a tale of dedicated healthcare workers, tirelessly working on the frontlines to bring care and compassion to those who need it most. And it is a narrative of empowerment, as individuals and families are given the tools and knowledge to take charge of their own health and well-being.

As we delve deeper into this case study, we uncover the intricacies of strategic partnerships and the power of technological innovation in reshaping healthcare landscapes. The collaboration between PIH, the Ministry of Health of Lesotho, and Qure.ai serves as a shining example of what can be achieved when diverse expertise and resources are brought together in the pursuit of a common goal. It is a model for global health initiatives, demonstrating that by harnessing the potential of AI and fostering strong partnerships, we can make significant strides towards eliminating tuberculosis and enhancing overall health outcomes.

The story of Lesotho's healthcare revolution is one of hope, determination, and the unyielding human spirit. It is a reminder that even in the face of daunting challenges, change is possible when we dare to dream, innovate, and collaborate. As we witness the transformative impact of AI-powered solutions like Qure.ai's qXR algorithm, we are inspired to envision a future where access to quality healthcare is not a privilege, but a fundamental right for all.

In the mountains of Lesotho, a quiet revolution is indeed unfolding – a revolution that holds the promise of a brighter, healthier tomorrow. With each scan processed, each potential TB case identified, and each life touched by this innovative approach to healthcare, Lesotho moves closer to turning the tide against tuberculosis and rewriting its health narrative. And as the world watches, this small nation in southern Africa stands tall, a beacon of hope and a testament to the transformative power of AI in the quest for global health equity.

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Transforming Healthcare in Lesotho with AI: A Case Study on Combating Tuberculosis 

Qure.ai has launched a five-point guide to steer UK NHS Trusts and Imaging Networks through the practicalities of activating Artificial Intelligence (AI).&nbsp;&nbsp;

The first point in the guide focuses on clinical considerations during the deployment cadence. It emphasizes the importance of aligning AI implementation with clinical goals and workflows, ensuring that the technology seamlessly integrates with existing practices and enhances patient care. By carefully considering the clinical aspects, healthcare providers can maximize the benefits of AI while minimizing disruption to their daily operations.

The second point addresses the crucial aspects of information governance and compliance with mandatory processes. AI deployment in healthcare requires adherence to strict data protection regulations and ethical guidelines. The guide provides insights into navigating these requirements, ensuring that patient privacy and data security remain top priorities throughout the deployment process.

Thirdly, the guide delves into the intricacies of IT integration, highlighting the significance of collaborating with hospital IT teams. Seamless integration of AI solutions with existing hospital systems is essential for efficient data flow and interoperability. The guide offers practical advice on fostering strong partnerships between AI providers and hospital IT departments, ensuring a smooth and successful integration process.

User training and patient awareness form the fourth point of the guide. Effective AI deployment relies on the readiness and competence of healthcare professionals to utilize the technology effectively. The guide provides strategies for comprehensive user training programs, equipping radiology staff with the necessary skills and knowledge to leverage AI to its fullest potential. Additionally, it emphasizes the importance of patient education and awareness, ensuring that patients understand the role of AI in their diagnostic journey and feel confident in the technology's capabilities.

Finally, the guide addresses the critical aspects of testing, go-live, and ongoing evaluation. It outlines a structured approach to thoroughly test AI solutions before live deployment, ensuring their accuracy, reliability, and robustness. Once the AI is activated, the guide recommends continuous monitoring and evaluation to assess its impact on clinical outcomes, efficiency, and patient satisfaction. This ongoing assessment enables healthcare providers to make data-driven decisions and refine their AI strategies over time.

"Demystifying AI Deployments" serves as an invaluable resource for radiology individuals and imaging departments planning for AI activation and deployment. By addressing key questions such as what comes first in AI deployment and who does what, the guide provides a clear and actionable framework for successful AI implementation. It empowers healthcare providers to navigate the complexities of AI adoption, ensuring a smooth and efficient transition towards enhanced diagnostic capabilities.

As the healthcare landscape continues to evolve, the integration of AI in radiology holds immense potential for improving patient outcomes, optimizing resource utilization, and advancing medical research. Qure.ai's five-point guide is a testament to their commitment to supporting healthcare providers in harnessing the power of AI, ultimately benefiting patients and transforming the future of diagnostic imaging.

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Qure.ai’s five-point guide to AI deployment in healthcare

This guide is dedicated to advancing lung health diagnostics through AI-enabled chest X-ray screening, bringing this innovative approach to the forefront of primary healthcare.

Chest X-rays, as recommended by the WHO, are a cornerstone in detecting common lower respiratory diseases such as pneumonia, TB, and COPD, particularly in primary care environments. Despite their widespread availability, the interpretation of these X-rays necessitates specialized radiologists, a resource that is markedly scarce in many global regions. This shortage not only impedes timely diagnosis but also escalates treatment costs and increases mortality risks.

Recognizing the critical need for skilled professionals, advanced diagnostic facilities, and the right technological tools, Qure's TB Reach Wave 11 initiative has been meticulously designed to simplify your decision-making process in selecting the most effective diagnostic tools. Our focus on artificial intelligence (AI) offers a pathway to assist clinicians in expediting diagnosis, thereby diminishing the duration and complexity of both investigation and treatment.

Explore the transformative potential of AI in enhancing your lung disease detection capabilities. We invite you to access our comprehensive support document and join us in this pivotal journey towards improved healthcare outcomes.

Fill out the form below for the full document:

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Qure.ai: TB REACH Wave 11 Support Document

Qure.ai Technologies Limited is committed to achieving Net Zero Emissions by 2050

Baseline Emissions Footprint Baseline emissions are a record of the greenhouse gases that have been produced in the past and were produced prior to the introduction of any strategies to reduce emissions. Baseline emissions are the reference point against which emissions reduction can be measured.&nbsp; BASELINE YEAR: H1 FY24 Qure.ai Technologies Limited is incorporated in the UK in 2021 and has not published carbon emissions for the years FY22 and FY23. Qure UK is a fully owned subsidiary of Qure.ai India. Qure India has started assessing carbon emissions from FY24 and have published our first Carbon&nbsp;

Reduction Plan for H1 FY24. Regarding scope 1 emissions, Qure.ai's services are directly delivered on AWS as a software. So, technically we have Zero scope 1 emissions at this point of time.&nbsp;

Baseline Year Emissions.webp

Carbon reduction overview.webp

Current Year Emissions Reporting (Same as baseline year emissions)

Reporting Year Emissions.webp

Qure.ai is a growing organisation and has been expanded rapidly in the last 5 years. We went from less than 30 employees and 10 deployments in 2017 to more than 300 employees and 1600+ sites across 80+ countries by 2023. This depicts the rate at which Qure is growing and we have been aggressively investing in human and technical resources. We can foresee Qure growing at this pace for the next 5 years and expecting a net positive carbon emissions.&nbsp;

However, Qure is committed to Net Zero carbon emissions and have started implementing multiple sustainable and eco-friendly initiatives across various business operations.&nbsp; Carbon Emission Projection: H1 FY29

Carbon emssio projection H1 FY29.webp

During the next 5 years we will introduce the following ESG initiatives:

From Insight to Impact: Our Case Studies