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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

AI in Action: Transforming Health Outcomes Across India’s Care Spectrum’ is a consolidated impact report from Qure.ai, launched at the India AI Impact Summit. the report outlines 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 has a curated collection of 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.

Fill the form to download the full report.

Fill the form to access the full report

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India Impact Report 

Looking back on FY 2024–25, what stands out most is not just how far&nbsp;Qure.ai&nbsp;has come, but how many lives this collective effort has been able to touch. The past year reinforced why we do what we do, building technology that strengthens healthcare systems and helps clinicians act earlier, faster, and with greater confidence. At&nbsp;Qure.ai, our purpose continues to guide every decision we make: harnessing artificial intelligence to close gaps in care and bring timely diagnosis within reach, no matter where a patient lives.

FY 2024–25 marked a defining chapter in that journey. This year,&nbsp;Qure.ai’s AI solutions reached more than 32 million lives, expanding our footprint to over 4,500 healthcare facilities across 100+ countries. Behind every statistic lies a human story, a diagnosis made earlier, a treatment started sooner, a life changed because technology met care at the right moment.

Our impact in global health continued to deepen. qXR screened over 7 million people for tuberculosis in FY 24–25 alone, flagging more than 6,50,000 individuals at risk, many in settings where access to radiologists, internet connectivity, or even stable electricity remains limited. From mobile screening vans in Nigeria and retrofitted X-ray machines in Kenya, Malawi, and liberia our AI-enabled faster diagnosis, reduced costs, and helped bring the “missing millions” into care. Independent evidence reaffirmed this impact, demonstrating higher TB notifications and meaningful cost savings for national health systems.

This year also saw significant advances in lung cancer detection, an area where late diagnosis remains one of healthcare’s most persistent challenges. As health systems worldwide look for scalable ways to identify disease earlier, AI-enabled chest X-rays are emerging as a powerful tool for change. In partnership with AstraZeneca and as part of the EDISON Alliance’s 1 Billion Lives Challenge, we surpassed 5 million people screened for lung cancer across 20 countries. Evidence from the CREATE study proved that routine chest X-rays, when augmented by AI, can become powerful tools for early intervention. From nationwide programs in El Salvador and Malaysia to expanding adoption across the United States, we are helping health systems shift from reactive diagnosis to proactive care.

In Neurocritical care, our AI solutions continued to prove that time truly matters. qER supported the screening of over 5,30,000 patients this year, flagging 65,000 critical findings and enabling faster triage in emergency settings. In&nbsp; Punjab, India, AI-powered hub-and-spoke stroke pathways reduced treatment delays and brought specialist-level care closer to patients, improving outcomes when every second counted.

Beyond scale, FY 24–25 was a year of milestones. We took AI-powered screening to new heights, literally, achieving the world’s highest-altitude chest X-ray screening at Everest Base Camp. We closed a $65 million Series D funding round, strengthening our ability to invest in science, people, and long-term impact. We received new regulatory clearances, published high-impact clinical evidence, and were recognised among TIME’s 100 Most Influential Companies of 2025, reaffirming&nbsp;Qure.ai’s global leadership in responsible, evidence-driven healthcare AI.

Perhaps most importantly, we continued to build for the future. With the launch of Aira, our AI co-pilot for frontline health workers we are moving beyond standalone tools toward integrated digital health ecosystems, designed to support primary care, strengthen national programs, and amplify human capability where it is needed most.

As we step into the next year, we carry a deep sense of responsibility to our partners, to health systems, and most importantly, to the millions of patients who rely on early and accurate diagnosis. None of this progress would be possible without the commitment of our teams and partners, the trust of governments and clinicians, and the shared belief that technology must always serve people.

Thank you for being part of this journey. Together, we are not only advancing artificial intelligence in healthcare, we are redefining access, strengthening systems, and shaping a future where early detection becomes the norm, not the exception.

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Qure.ai FY 24-25 Impact Report: Global AI Healthcare Innovations

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 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.

Complete the form to access the full report


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

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.

Fill out the form to access the guide

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

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;

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Current Year Emissions Reporting (Same as baseline year emissions)

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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

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

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Activities which qure will take up: 1. Renewable-Powered Data Servers: Qure.ai is committed to sustainability by investing in data servers powered by renewable energy sources. This strategic choice significantly reduces our scope-2 carbon footprint.

2. Sustainable Procurements: We actively engage with vendors who share our mission of achieving carbon neutrality by 2050,ensuring that our supply chain aligns with our environmental goals.

3. Green Travel and Commute: We promote sustainability by encouraging electric and renewable energy sources for employee travel and commuting, thereby reducing our carbon emissions.

4. Solar-Powered Office: Qure.ai is taking steps to make one of its offices run entirely on solar energy, contributing to clean and green operations.

5. Eco-Friendly Technology: In our pursuit of environmental responsibility, we invest in eco-friendly technologies to power our computing infrastructure, making a positive impact on the environment.

6. Employee Engagement: To foster a culture of sustainability, we conduct training sessions to educate employees about the importance of environmental stewardship. We encourage employees to propose green initiatives and practices, making sustainability a part of our organizational DNA.

7. Carbon Offset Initiatives: In our commitment to carbon reduction, we invest in carbon offset projects, such as reforestation and renewable energy initiatives. We also explore partnership opportunities with environmental organizations and join carbon offset programs to contribute to a greener planet.

Establishing Our ESG Core Team

At Qure.ai, we consider sustainability to be more than a mere buzzword. It's a fundamental commitment that we are passionate about. To ensure that our dedication to Environmental, Social, and Governance (ESG) principles goes beyond empty rhetoric and transforms into impactful actions, we have established our ESG Core Team. The idea behind this team was to incorporate sustainability practices into our operational fabric, as envisioned by our leadership.&nbsp;

The ESG Core Team comprised of cross-functional experts from our executive leadership team pledges to reduce our carbon footprint, champion ethical and responsible business practices, and promote a culture of inclusivity and equity. This is the start of a journey toward a sustainable and equitable future, with the ESG Core Team leading the way and ensuring that every step we take embodies ESG values.&nbsp;

Currently, the key commitee members include:&nbsp;

1. Bhargava Reddy, Chief Operating Officer&nbsp;

2. Anushree Saha, General Counsel &amp; Company Secretary&nbsp;

3. Sonu Vijan, AVP, Travel &amp; Admin&nbsp;

4. Anurag Sharma, Manager, Legal Affairs and Strategy&nbsp;

5. Bunty Kundnani, Chief Regulatory Officer&nbsp;

6. Dhruv Shah, Director, Business Intelligence &amp; Operations&nbsp;

7. Divya Gupta, Chief Growth Officer&nbsp;

8. Poonam Ajgaonkar, Chief People Officer&nbsp;

9. Saniya Pawar, VP, Impact &amp; Evidence&nbsp;

This Carbon Reduction Plan has been completed in accordance with PPN 06/21 and associated guidance and reporting standard for Carbon Reduction Plans.&nbsp;

Emissions have been reported and recorded in accordance with the published reporting standard for Carbon Reduction Plans and the GHG Reporting Protocol corporate standard 13 and uses the appropriate Government emission conversion factors for greenhouse gas company reporting.&nbsp;

Scope 1 and Scope 2 emissions have been reported in accordance with SECR requirements, and the required subset of Scope 3 emissions have been reported in accordance with the published reporting standard for Carbon Reduction Plans and the Corporate Value Chain (Scope 3) Standard.&nbsp;

This Carbon Reduction Plan has been reviewed and signed off by&nbsp; Mr. Bhargava Reddy, Chief Operating Officer, Qure.

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https://ghgprotocol.org/corporate-standard https://www.gov.uk/government/collections/government-conversion-factors-for-company-reporting https://ghgprotocol.org/standards/scope-3-standard&nbsp;

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Qure.ai's Carbon Reduction Plan

Artificial Intelligence (AI) is redefining precision diagnostics and early detection of multiple diseases, including cancer, neuro-critical conditions, cardiovascular myopathy, and many more. In radiology, AI is used varyingly – its application is being experimented with across the healthcare dissemination pathway to identify the optimal implementation and deployment methodology.&nbsp;&nbsp;

AI solutions, while being highly agile in screening and detection of abnormalities, can also be successfully deployed to optimize radiologists' workflows, facilitate quantitative radiology, and assist in the triage of critical cases. Finally, with the pandemic also weighing in on the current healthcare infrastructure, we can conclude that AI-enabled healthcare will eventually replace legacy infrastructure. &nbsp;&nbsp;

The&nbsp;<a href="https://www.thelancet.com/journals/landig/article/PIIS2589-7500(20)30160-6/fulltext">Lancet reports</a>&nbsp;that medical investigations leveraging computer-aided diagnostics (CAD) have shown excellent accuracy, sensitivity, and specificity for detecting minor radiographic abnormalities, potentially improving public health. It further states that AI could identify imaging pattern changes that are not readily amenable to human identification.&nbsp;&nbsp;

Earlier this year, the United Kingdom declared its goal of harnessing digital expertise and Artificial Intelligence (AI) to drive transformation within the NHS and social care. Similar adoption models are being discussed in hospitals and healthcare networks across the globe. At present, the workload on the radiology workforce is staggering, with a radiologist required to read a scan every 3-4 seconds. An AI-enabled workflow can alleviate this issue. Moreover, it can help bring down the intra and inter-reader variations. AI solutions can also help use radiology to detect numerous abnormalities early that can directly impact patient prognosis. &nbsp;&nbsp;

While the need for intelligent technology has been established, questions on how, what, and where, remain an open-ended discourse across the medical fraternity. As a result, not much historical data will come into play when an organization decides to implement AI within the system, which is where the collective knowledge of clinicians, radiologists, technologists, and AI solution providers come together. It is the premise of Qure.ai's eminent&nbsp;<a href="https://youtu.be/l8zRXDlhJ2w">panel of experts</a>&nbsp;on AI implementation including:&nbsp;&nbsp;

Step # 1: Identify and isolating the current bottlenecks

It can vary across the set-up of your organization, access to domain experts, and the use case you have identified. For example, at a teaching hospital, AI-enabled data mining may not be a priority as much as resolving the resource crunch and workforce planning. Whereas if you belong to academia, then this becomes your priority. A significant step in seamless implementation is to assemble the right team to implement the project and see to it – end to end. Deploying AI is not a pet project but a large-scale deployment that should integrate with your long-term goal. Getting all the stakeholders, including data governance, IT services, and the chief executive members, on the same page will help in the long run. &nbsp;&nbsp;

Step #2: Identify the right AI vendor for you&nbsp;&nbsp;

With multiple vendors available for similar solutions, industry-approved, clinically validated products should be your go-to option. Though AI is now being sold as a pattern recognition solution, building trust for the technology within the workforce should be your priority to enable them to rely on it as needed. Deploying AI for triage and acting as quality assurance is an excellent place to start. Check their peer-reviewed data and the status of their CE/FDA clearance. Lastly, run a pilot and get your success metrics clearly defined before any deployment. Any implementation is gauged as a success when well-defined success criteria are in place. Having a clear end goal – lives saved, time saved and/or money saved, needs to be obvious to understand the ROI of the solution.&nbsp;&nbsp;

Step #3: Evaluate if the solution solves for your business use case&nbsp;

If you are a teleradiology company looking for AI solutions, a whole new set of questions arises. While most points discussed above, hold true for a teleradiology context as well, like data privacy and FDA/CE clearance, and the host of peer-reviewed data to back an AI solution's precision and read accuracy, a teleradiology company will face more challenges when it comes to integrating the solution across their deployed sites. Unlike a hospital, where the deployment is singular, a teleradiology company will require a customized integration plan for every client site. The challenge heightens if they have multiple PACS vendors in place. When choosing a vendor, they will depend on the vendor's training data's transparency, integration agility, and customizable solutions and markers. 

Step #4: Check for Regulatory Compliance&nbsp;&nbsp;

Experts have weighed in on the need for a single AI database. While the European market is getting ready to publish EUDAMED, the already available ECLAIR guidelines for choosing your AI partner will be the right place to start if you identify and deploy an AI solution in the EU region. While CE/FDA clearances are non-negotiable, it is equally vital that you understand the premise of these certifications.&nbsp;&nbsp;

Every AI solution that is CE/FDA cleared has an intended use statement and instructions to use a manual that is regulatory approved. While the vendor may have more to claim than what is present in these documents, you must do the due diligence to see if your problem statement matches your chosen partner's CE/FDA-marked intended use. Similarly, it is essential to see how compatible the chosen AI solution is with your data. Identifying the pre-determined biases and margins of error of a particular solution concerning your clinical data before deployment will help bring down false-positive rates and AI biases. Most vendors have ample documentation citing the same. Looking through their categorization of the solution's training database will also give you a clearer picture of what to modify when it comes to deployment.&nbsp;

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Qure for Sure: The definitive guide to implementing AI in your NHS Trust

At&nbsp;<a href="https://london.intelligenthealth.ai/">Intelligent Health UK 2022</a>, some of Qure.ai's notable partners and clients shared their expertise &amp; insights on evaluating &amp; implementing Artificial Intelligence solutions in&nbsp;<a href="https://www.nhs.uk/">NHS Trust healthcare institutions</a>. The eminent panellists included Dr.&nbsp;<a href="https://www.linkedin.com/in/dr-hugh-harvey-58a470112/?original_referer=https%3A%2F%2Fwww%2Egoogle%2Ecom%2F&amp;originalSubdomain=uk">Hugh Harvey</a>, Dr.&nbsp;<a href="https://www.linkedin.com/in/amrkum/">Amrita Kumar</a>,&nbsp;<a href="https://www.linkedin.com/in/emma-hughes-733b9a54/">Emma Hughes</a>, Dr.&nbsp;<a href="https://garrypettet.com/">Garry Pettet</a>&nbsp;and Matthew Watt. Some of the key topics covered:

Following the key topics covered, the panellists delved deeper into the practical aspects of AI adoption. They emphasized the importance of identifying the specific clinical challenges that AI can address within a healthcare institution. By clearly defining the problem and understanding the potential impact of AI, organizations can make informed decisions about which solutions are most suitable for their needs.

The panellists also discussed the critical factors to consider when choosing an AI solution. They highlighted the significance of evaluating the solution's clinical validation, regulatory compliance, and alignment with the institution's existing workflows and infrastructure. Engaging with vendors who have a proven track record of successful implementations and a deep understanding of the healthcare domain was deemed essential.

Once a suitable AI solution has been identified, the panellists emphasized the importance of involving key stakeholders in the adoption process. This includes clinicians, IT departments, information governance (IG) teams, and patient representatives. By fostering collaboration and open communication among these stakeholders, healthcare institutions can ensure a smooth and successful integration of AI into clinical practice.

The panellists also provided guidance on evaluating and procuring AI solutions. They stressed the need to assess the return on investment (RoI) by considering factors such as improved patient outcomes, increased efficiency, and cost savings. Engaging with procurement teams early in the process and understanding the requirements for data privacy, security, and interoperability was deemed crucial.

Furthermore, the panellists highlighted the importance of ongoing monitoring and evaluation of AI solutions post-implementation. By establishing clear metrics and key performance indicators (KPIs), healthcare institutions can assess the impact of AI on clinical outcomes, operational efficiency, and patient satisfaction. Regular feedback loops and continuous improvement processes were recommended to ensure the long-term success and sustainability of AI adoption.

Throughout the discussion, the panellists emphasized the need for a holistic approach to AI implementation. This involves not only the technical aspects but also the cultural and organizational changes required to support the integration of AI into clinical workflows. Providing adequate training and support for healthcare professionals, as well as engaging patients and the wider community, was considered essential for building trust and confidence in AI-enabled healthcare.

The insights shared by the panellists at Intelligent Health UK 2022 provide a roadmap for NHS Trust healthcare institutions embarking on their AI journey. By carefully evaluating clinical needs, selecting appropriate solutions, engaging stakeholders, and ensuring ongoing monitoring and improvement, healthcare organizations can successfully harness the power of AI to enhance patient care, improve operational efficiency, and drive innovation in healthcare delivery.

As the adoption of AI in healthcare continues to gain momentum, the experiences and best practices shared by the panelists serve as valuable guidance for NHS Trust healthcare institutions. By learning from the successes and challenges of early adopters, organizations can navigate the complexities of AI implementation and unlock the full potential of this transformative technology in improving patient outcomes and advancing healthcare delivery.

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AI – Does your Trust need it? Here’s how to get it right the first time IHUK22

Dr Hugh Harvey speaks about How AI will fundamentally change the Health Care Delivery in the NHS Trust Hospitals.

In a recent interview, we had the opportunity to speak with Dr. Harvey, a seasoned medical professional with a diverse background in the field of healthcare. Dr. Harvey began his career as a clinician in the NHS, working his way up to become a consultant radiologist. After that, he pursued a research degree at the Institute of Cancer Research and more recently, he has worked at two startups focused on AI in healthcare.

During the conversation, Dr. Harvey discussed the ECLAIR guidelines, a set of recommendations developed by academics and industry experts to help hospitals evaluate AI systems from vendors. These guidelines provide a structured approach for hospitals to assess the intended use, potential benefits and risks, and financial considerations of AI products.

When looking at an AI vendor, Dr. Harvey emphasized the importance of understanding the target population, conditions, and usage environment of the product. Hospitals should also review the Benefit-Risk Analysis Matrix to evaluate the expected risks and benefits. Additionally, financial considerations are vital, and hospitals should assess the economic impact, including initial costs and potential savings or improvements in care quality.

Speaking about his collaboration with Qure.ai, Dr. Harvey explained that they are analyzing different pathways and their financial implications, aiming to understand how Qure.ai's products can improve patient quality of life and lead to cost savings for NHS Trusts.

Finally, Dr. Harvey shared his insights on the trends in AI and healthcare. He believes that AI is poised to significantly change how we deliver healthcare, particularly in data-driven fields like radiology, ophthalmology, and pathology. However, he stressed the importance of proceeding cautiously, conducting thorough validation, and involving patients and the public in the process to ensure a careful and responsible implementation of these technologies.

Overall, Dr. Harvey's insights provide valuable guidance for healthcare organizations navigating the complex landscape of AI in the medical field.

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How AI will fundamentally change healthcare delivery

The Ministry of Health, Oman’s Covid-19 monitoring platform, known as ‘Tarassud Plus’, is used as monitoring system for diagnosing, following up, and tracking the medical condition of individuals infected with COVID-19 under quarantine, by using artificial intelligence and advanced tracking technologies.

The world has been battling with COVID-19 since the past two years. Both public and private health systems across the world are adopting different strategies to put an end to the spread of the pandemic and save the lives of people. Despite several novel strategies and solutions; isolating and contact tracing individuals continues to remain a challenging task.

During the first wave of the pandemic, shortage of medical resources was a universal challenge due to exponential increase of infected people in a short time. Remote patient management became the need of the hour, but the shortage of medical staff for timely monitoring of quarantined individuals remained a challenge. The qScout platform developed by Qure.ai was adopted by the Ministry of Health Oman, for contact monitoring and remote patient management at a national scale. It was also integrated withthe government health surveillance platform Tarassud to give population level alerts to authorities.

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, thereby minimizing and scheduling visits to medical institutions, and focusing only on cases that need a medical examination. The phone based chatbot, deployed within the Tarssud Plus app, communicated through regular interval questions which the individuals could respond with clickable options for ease of use. The chatbot is interactive and its questions are designed to keep it user friendly.

qScout developed by “Qure.ai” in partnership with Al Burkan Company was used to remotely monitor individuals to check for worsening of their medical condition on a daily basis. This platform helped alleviate the burden of health workers and control the spread of the pandemic.

The information gathered was processed using algorithms in the backend to assess the risk factors. This information was then relayed back to the Tarassud Plus platform to indicate risk categories.

Over a span of 8 months, 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.

Using data mining, the system could also estimate the potential surge in cases across regions of the country, helping health workers and government monitor hotspot regions and prepare for receiving cases.

The MOH also provided a wearable gadget that sent real-time information to the competent authorities about the movements and locations of a quarantined or infected person. It could also send alerts if this person left their location or tried to remove the gadget.

Through managing symptoms and triaging peopleremotely using the AI-powered tool, Qure.ai was able to help the Ministry of Health Oman ensure that individuals are only brought to the hospital at the right time, minimizing panic and optimizing utilisation of resources.

The modularity and integration capability of qScout with various web/mobile applications, interoperability built in from inception facilitates enrolment and engagement with millions of users via the Tarassud platform.

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MoH, Oman uses qScout for patient monitoring and population surveillance​

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