image-150-64c8cd514b55a.webp

image-151-64c8cd518a917.webp

group-1000002623-64c8cd4f8d576.webp

image-146-64c8cd50567b2.webp

image-147-64c8cd501e463.webp

image-148-64c8cd50b2c5c.webp

image-149-64c8cd50d627e.webp

BBC-Logo.webp

The-Independent-Logo.webp

Featured in

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

Newly accredited training program equips imaging related professionals with the knowledge and skills to maximize return on AI investment&nbsp;&nbsp;

To prepare healthcare workforces and providers for an AI-driven future, Qure.ai has expanded its Global AI Super User Training, to the United States. It has received approval from the American Society of Radiologic Technologists (ASRT). The Super User training equips Healthcare Professionals with the knowledge and skills to effectively apply AI in practice, transform clinical operations, optimize patient care, gain a solid return on AI investment, and foster positive partnerships within the medical community.&nbsp;

The <a href="https://www.qure.ai/us" target="_blank">Qure.ai USA</a> Super User initiative builds on global success in regions such as the UK and its National Health Service (NHS). ASRT has approved the program for Category A CE credits, granting participants 4 Continuing Education (CE) credits for course completion. This recognition aligns with the American Registry of Radiologic Technologists’ (ARRT) rigorous standards for professional development.&nbsp;

“Our expansion of the AI Super User Training program represents Qure.ai’s dedication to continuous learning and professional development within the imaging community,” said Samir Shah MD, Chief Medical Officer at Qure.ai. “With educational endorsements, we are now able to deliver formalized, professionally recognized training directly to hospitals, providing imaging professionals with an opportunity to gain CE credits while enhancing their skills in AI implementation and scaling adoption. By investing in the ongoing education of these caregivers, we can leverage AI as a transformative force, driving impactful partnerships within clinical environments.”&nbsp;

The Super User Training Program will have a critical focus on understanding how AI tools are integrated into the existing radiology workflows, including their intended use, strengths, and constraints. Participants will also engage with the regulatory and ethical frameworks governing AI deployment, alongside protocols for clinical review and post-market surveillance. The importance of patient and public involvement in AI-driven initiatives will be highlighted. The program will also include a practical demonstration of the deployed system in a clinical setting.&nbsp;

“This program is designed to build a foundational understanding of AI and its evolving role in radiology. AI is reshaping radiology fast and users need to be at the centre of that shift. This program is built to give, not just a working knowledge of AI, but the confidence to use it, and lead its integration into clinical practice”, said Shamie Kumar, Senior Director and Radiographer, Qure.ai.&nbsp;&nbsp;

The Qure.ai Super User endorsements in the US validate educational quality and professional value. These accreditations ensure radiographers and radiology technicians are equipped to integrate AI into their practices confidently, supporting digital evolution while fulfilling Continuing Education and professional development obligations.&nbsp;

large_IMG_5533 (1).webp

medium_IMG_5533 (1).webp

small_IMG_5533 (1).webp

thumbnail_IMG_5533 (1).webp

IMG_5533 (1).webp

Qure.ai introduces Lung Cancer AI training with ASRT approval to support USA deployments

Leveraging its strength in digital health innovation, <a href="https://www.qure.ai/" target="_blank">Qure.ai</a> has launched a new AI-powered co-pilot tool for frontline healthcare workers in resource-constrained geographies this week during the 78th World Health Assembly in Geneva.&nbsp;

‘<a href="https://about-aira.qure.ai/" target="_blank">AIRA</a>’ is designed to optimize limited healthcare resources in Low- and Middle-Income Countries (LMICs) by supporting AI-enabled digitization of symptoms and patient history collection; clinical protocol adherence and decision support; and aggregated population health insights.&nbsp;

There are 17 million preventable deaths in LMICs and an estimated shortage of 11 million health workers by 2030. At the same time, more than 40% of community health workers’ time is spent on manual data collection, and yet countries do not have population-level data to make informed decisions. AIRA aims to solve this urgent need by freeing up precious health worker time to engage more with patients, while digitizing data automatically.&nbsp;

Speaking at the World Health Assembly side-event on AI, Prashant Warier, CEO and Founder of Qure.ai, said, “With AI, we can make a seismic shift towards health equity in LMICs. AIRA in the hands of every healthcare worker will free up their time for more patient interactions via automated data collection and better clinical protocol adherence. With AI, we can multiply every dollar spent and realize significantly more impact and returns in LMIC health systems. We have demonstrated this in our last 10 years in TB and are motivated to do the same now for primary healthcare.”&nbsp;

Dr. Michel Sidibé, Special Envoy at the African Union, said, “Health ministries in developing nations need to deliver healthcare to their populations at a fraction of the budget compared to developed countries. We have to be creative to make this happen. Digital health and AI are most certainly catalysts to improve efficiency, access, and quality of care.” &nbsp;

AIRA is an AI co-pilot for healthcare workers in LMICs. It is built on Large Language Models (LLMs) with a deep understanding of Low- and Middle-Income Country health systems and needs. It is designed to reduce administrative workload and free up time for better patient care, while enabling better protocol adherence and population insights.

<a href="https://www.who.int/health-topics/health-workforce#tab=tab_1">https://www.who.int/health-topics/health-workforce#tab=tab_1</a>

large_Updated Aira PR thumbnail.webp

medium_Updated Aira PR thumbnail.webp

small_Updated Aira PR thumbnail.webp

thumbnail_Updated Aira PR thumbnail.webp

Updated Aira PR thumbnail.webp

Qure.ai Launches AIRA for LMIC Health Workers at WHA 2025

Mumbai, India, May 8, 2025: Johnson &amp; Johnson MedTech, a global leader in surgical technologies andsolutions, has onboarded Qure.ai, a global leader in artificial intelligence (AI) for healthcare, as a strategicpartner with Johnson &amp; Johnson Private Limited, a Johnson &amp; Johnson company, to enhance earlydetection of lung cancer in India. This collaboration brings together cutting-edge AI and medical technology, helping identify lung cancer at its most treatable stage.

This initiative is part of Project BreatheEZ, a broader strategic collaboration between Qure.ai and Johnson &amp;Johnson MedTech, and designed to establish AI-led Incidental Pulmonary Nodule (IPN) Detection clinicsacross leading hospitals in India. These clinics will act as integrated screening hubs, optimizing earlydetection, triaging, and follow-up care for lung cancer patients. As part of this collaboration, Qure.ai’s AItechnology will be deployed across 10 hub medical centers in India, with an additional 20 supporting spokesites. The first such clinic has been launched in Thangam Cancer Centre in Namakkal, Tamil Nadu.

In India, one in nine persons is likely to be diagnosed with cancer in their lifetime. It is an increasing healthconcern, and the projected cancer burden is expected to rise from 26.7 million DALYs (Disability-AdjustedLife Years) in 2021 to 29.8 million in 20251. This growing health challenge needs innovative solutions toimprove early detection and ultimately save lives. Traditional diagnostic methods often fail to detect lungcancer at an early stage, leading to delays in treatment. Thus, this collaboration between Johnson &amp;Johnson MedTech and Qure.ai marks a significant leap forward.

By harnessing artificial intelligence in the modalities of X-Ray &amp; CT scans, Johnson &amp; Johnson MedTechIndia &amp; Qure.ai are enabling the detection of potential lung nodules that might otherwise be missed. This happens through flagging risky nodules in X-Rays and CT Scans that can potentially turn out to be malignant. It also introduces the concept of structured IPN clinics where there is a proactive impetus towards incidental screening of early-stage lung cancer. This partnership embodies Johnson &amp; Johnson MedTech’s commitment to enhancing early lung cancer detection, ultimately transforming the standard of lung cancer care.

Anuj Virmani, Managing Director, India, Johnson &amp; Johnson MedTech, said, “Lung cancer continues to be one of the leading causes of cancer in both men and women. In India, where access to advanced healthcare facilities is often limited, especially in tier-2 and tier-3 cities, patients face significant challenges in receiving timely and effective diagnosis, which further delays access to treatment. Our collaboration with Qure.ai is a testament to our commitment to advancing healthcare through innovative solutions, continues to drive impactful collaborations and integrating our solutions in lung cancer.”

1. ICMR and NCDIR World Cancer Day 2024, Close the care gap- Addressing cancer care in India, 04th&nbsp;- February – 2024 <a href="https://ncdirindia.org/display/wcd.aspx">https://ncdirindia.org/display/wcd.aspx</a>

large_Web Hero.webp

medium_Web Hero.webp

small_Web Hero.webp

thumbnail_Web Hero.webp

Web Hero.webp

Johnson & Johnson Medtech Partners with Qure.ai to Boost Early Detection of Lung Cancer in India

AstraZeneca, in partnership with health-tech company Qure.ai, today announced the successful completion of 5 million artificial intelligence (AI) enabled chest X-rays (CXRs) across more than 20 countries in Asia, the Middle East, Africa, and Latin America.  The milestone, part of AstraZeneca's commitment to the World Economic Forum's EDISON Alliance 1 Billion Lives Challenge, demonstrates the potential of AI to improve lung cancer detection, especially within resource-limited healthcare settings.&nbsp;

The AI-enabled CXRs revealed important findings, including lung nodules at high risk for cancer in nearly 50,000 people – prompting their referral for further testing and possible diagnosis.&nbsp;&nbsp;

The EDISON Alliance's 1 Billion Lives Challenge, launched in 2022, aims to improve 1 billion lives through digital access to healthcare, education, and financial services. AstraZeneca supports the initiative, aligning with the goals of its <a href="https://tinyurl.com/5n8f7fje" target="_blank">A.Catalyst Network</a> – AstraZeneca’s global innovation network that aims to speed up the process of turning innovative ideas into real-world healthcare solutions.&nbsp;&nbsp;

In 2020, under the A.Catalyst Network initiative, AstraZeneca partnered with Qure.ai to harness Qure.ai's qXR® technology for assessing CXRs and determining potential lung cancer risk. This collaboration brings together diverse stakeholders across geographical boundaries to foster innovation throughout the patient journey. By using AI to analyse routine X-rays for risks of cancer, healthcare professionals can focus on those patients who need further assessment, such as a low-dose CT scan to confirm or rule out lung cancer. This is especially helpful in countries where resources are limited, as it helps to make the best use of available equipment and expertise, ensuring that those at highest risk get the attention they need and that screening programs are as effective as possible.&nbsp;

"Reaching this milestone underscores our commitment to driving progress towards early detection, the first step on the path to ultimately improved patient outcomes," said Ti Hwei How, Vice President, International Oncology, AstraZeneca. "Our collaboration with Qure.ai has validated the power of AI-enabled chest X-rays as a cost-effective triaging tool for early lung cancer detection. With successful implementation in countries such as Colombia, El Salvador and India, we are setting the stage for scaling this approach. We are actively partnering with Ministries of Health and policymakers to prioritise lung health and lung cancer on national agendas, including through AI-enabled screening programs to make a real difference.” &nbsp;

"This collaboration between AstraZeneca and Qure.ai exemplifies the EDISON Alliance's vision of leveraging digital innovation to address critical healthcare challenges," said Cindy Hoots, Chief Digital Officer and Chief Information Officer, AstraZeneca, and Deputy to AstraZeneca’s Chair and ‘Champion’ of the Alliance. It showcases how partnerships can accelerate the delivery of potentially life-saving technologies, particularly in regions where access to advanced screening is limited.&nbsp;&nbsp;

Lung cancer is the leading cause of cancer-related deaths worldwide, and while mortality rates are generally declining in high-income countries, they are rising in low-and-middle-income countries (LMICs). Early detection through screening plays a critical role in reducing lung cancer deaths by diagnosing more lung cancers at an early stage when they are still curable.

"Five million scans globally is a significant achievement, demonstrating the scalability and effectiveness of AI in improving lung cancer screening in resource-limited settings” said Prashant Warier, CEO and Founder, Qure.ai. "Partnering with AstraZeneca has enabled early adoption and scale of our AI-powered solutions and helped to drive the evidence generation required to support their integration into national health systems, ultimately helping to ensure that more patients receive the timely diagnosis and treatment they need." &nbsp;

This milestone adds to a growing body of evidence that demonstrates the utility of AI-enabled CXR triaging as part of resource-stratified lung cancer screening strategies. Data recently released at the European Lung Cancer Congress (ELCC) 2025 showed qXR® may be effective in detecting high-risk lung nodules 54.1% of the time for early detection of lung cancer, as well as the technology’s cost-effectiveness, based on data modelling its use within Vietnam’s healthcare system.

To find out more and gain your copy of an executive summary impact report detailing the 5 million scan achievement and real-world data, <a href="https://www.qure.ai/impact_stories/Unlocking-the-Power-of-AI-for-Early-Lung-Cancer-Detection">click here&nbsp;</a>

large_Lung Cancer-Web Banner-3.webp

medium_Lung Cancer-Web Banner-3.webp

small_Lung Cancer-Web Banner-3.webp

thumbnail_Lung Cancer-Web Banner-3.webp

Lung Cancer-Web Banner-3.webp

A new era for Lung Cancer Detection: AI-enabled risk assessment reaches 5 million people around the world

The Directorate of Health Services (DHS) in Goa has extended its partnership with AstraZeneca and Qure.ai for the Early Lung Cancer Detection Program, aimed at improving early diagnosis and treatment outcomes. The MoU was signed in the presence of Health Minister Vishwajit Rane, marking a two-year extension of the initiative.&nbsp;

Launched in June 2024, the program uses Qure.ai's artificial intelligence (AI) technology to screen chest X-rays for signs of lung cancer. Since its introduction, over 33,800 X-rays have been screened across 17 DHS centres, identifying 3,144 nodules, including 143 classified as high-risk. One confirmed lung cancer case has been detected through the program's referral system, involving physician reviews, CT scans, and biopsies.&nbsp;

Goa Health Minister, Vishwajit Rane emphasized the importance of early detection in reducing cancer-related deaths. "With the successful deployment of AI-powered tools, we are witnessing faster diagnosis and improved referrals. This partnership reinforces our commitment to preventive healthcare and enhancing Goa's public health system," he said.&nbsp;&nbsp;

Patients undergoing X-rays will now be mandatorily screened for lung cancer as part of the process at govt. hospitals.&nbsp;

The program also features Nurse Navigators who support high-risk patients, ensuring follow-up from screening to diagnosis. A strong referral network involving physicians, specialists, and diagnostic facilities has been established to streamline clinical interventions.&nbsp;

The extended partnership aims to expand screening efforts, improve patient tracking, and introduce new training modules for healthcare workers at DHS centres.&nbsp;

Read the full story here: <a href="https://goaplusnews.com/health-minister-vishwajit-rane-expands-ai-powered-lung-cancer-detection-program-in-goa/" target="_blank">https://goaplusnews.com/health-minister-vishwajit-rane-expands-ai-powered-lung-cancer-detection-program-in-goa/</a>&nbsp;

large_Goa Lung Cancer-05.webp

medium_Goa Lung Cancer-05.webp

small_Goa Lung Cancer-05.webp

thumbnail_Goa Lung Cancer-05.webp

Goa Lung Cancer-05.webp

DHS Goa Extends MoU with Qure.ai and AstraZeneca to Advance Early Lung Cancer Diagnosis 

Peninsula Imaging Network (<a href="https://peninsuladiagnostics.nhs.uk/imaging-home//" target="_blank">PenRAD</a>) consisting of four NHS Trusts in Devon, Cornwall and the Isles of Scilly, has gone live with the UK’s first commercial deployment of the <a href="https://www.qure.ai/" target="_blank">Qure.ai</a> Artificial Intelligence (AI) for chest CT (qCT). It aims to assist radiologists with the early detection and monitoring of lung nodules, that can be indicative of lung cancer.&nbsp;&nbsp;

The AI is currently processing around 1,200 Chest CT scans from patients each week across all four NHS trusts - Royal Cornwall Hospitals NHS Trust; Royal Devon University Healthcare NHS Foundation Trust; Torbay and South Devon NHS Foundation Trust; and University Hospitals Plymouth NHS Trust. The patient population supported are from a mix of coastal, rural and urban locations in the significantly sized Southwest England peninsula.&nbsp;&nbsp;

The Chest CT AI was implemented with funding from the government’s £21m Artificial Intelligence Diagnostic Fund (AIDF). PenRAD chose the qCT solution for its bid to the AIDF, in collaboration with Health Innovation Southwest and the Peninsula Cancer Alliance.&nbsp;

Tej Pandher, a Consultant Radiologist at University Hospitals Plymouth NHS Trust states, “Lung nodule AI assistance helps to identify and track suspicious nodules over time. The reporting radiologist can then put any such nodules into a clinical context and provide useful information for further follow up and/or treatment.”&nbsp;

“We are delighted to be live with qCT at PenRAD to support with the digital transformation of healthcare in the region and extend the potential of AI-powered early lung cancer detection. Lung cancer is the leading cause of cancer-deaths worldwide, with approximately 75% of patients detected in late-stage disease. Earlier detection can boost survival rates, by over 90% if treatment starts at stage 1,” states Surabhi Srivastava, UK Business Head at Qure.ai.&nbsp;&nbsp;

"qCT has been designed to provide clinical decision support in the detection, characterisation, quantification and monitoring of lung nodules. It can also pull patient images from prior examinations to provide comprehensive nodule management and support progression monitoring over time. This makes it easier for the clinician to assess the growth of nodules with standardised data for volumetry assessment and an auto assigned malignancy risk score of pulmonary nodules using the Brock model/ BTS Guidelines,” continues Surabhi Srivastava.&nbsp;&nbsp;

qCT from global healthcare AI innovator Qure.ai, is part of an end-to-end <a href="https://www.qure.ai/product/lung-nodule-management" target="_blank">AI-powered lung cancer care continuum</a> suite of solutions for chest X-ray and CT, to detect, measure and track lung nodules.

large_IMG_7090.webp

medium_IMG_7090.webp

small_IMG_7090.webp

thumbnail_IMG_7090.webp

IMG_7090.webp

PenRAD Imaging Network deploys AI-Powered Chest CT for early lung cancer detection and monitoring of lung nodules

New York, April 2, 2025:&nbsp;<a href="https://www.uhhospitals.org/about-uh">University Hospitals&nbsp;Cleveland Medical Center&nbsp;</a>(UH) has announced a groundbreaking collaboration with global healthcare Artificial Intelligence (AI) innovator&nbsp;<a href="https://www.qure.ai/">Qure.ai</a>&nbsp;to deploy chest X-ray AI supporting earlier identification of lung cancers.&nbsp;

The FDA cleared chest X-ray AI solution&nbsp;<a href="https://www.qure.ai/product/lung-nodule-management">qXR</a>-LN will act as a second read, to be compared to the radiologists’ read of patient chest X-rays for any suspicious lung nodules. This will also provide evidence for future AI research.&nbsp;

“Lung cancer remains the leading cause of cancer-related deaths in the United States. To improve early diagnosis and survival rates, current guidelines recommend low-dose CT (LDCT) lung cancer screening as the standard of care for high-risk individuals, such as smokers and former smokers. However,&nbsp;despite its proven benefits, CT screening uptake remains alarmingly low nationally — out of 100 eligible individuals, only about 16 actually undergo screening,” states&nbsp;Amit Gupta, MD,&nbsp;Division&nbsp;Chief of Cardiothoracic Imaging and Modality Director of Diagnostic Radiography at University Hospitals Cleveland Medical Center.

“One way to enhance lung cancer detection is by identifying early-stage lung nodules and cancers incidentally when patients undergo chest X-rays for other medical reasons during hospital admissions,” explains Dr. Gupta.

However,&nbsp;detecting pulmonary nodules on plain X-rays remains a significant challenge, as these subtle findings can be easily overlooked. “This not only poses a substantial&nbsp;burden&nbsp;but also impacts&nbsp;patient care,” he continues.

To address this issue, University Hospitals Cleveland Medical Center is conducting a clinical trial to further investigate the efficacy of the qXR AI algorithm, an artificial intelligence tool designed to enhance the detection of pulmonary nodules on chest X-rays, by comparing its ability to detect pulmonary nodules to a radiologist’s interpretation of those same chest X-rays.

“AI serves as an additional set of eyes for radiologists, enhancing detection by flagging lung nodules that may require further evaluation. This AI-driven approach may aid in identifying more nodules which we hope supports patient care and enables us to evaluate the broader impact of medical imaging AI,” says Dr. Gupta. “The clinical trial will evaluate how many patients require follow-up CT scans, biopsies, and how many more lung cancer cases are diagnosed earlier using AI. The hope is that this clinical trial will not only advance early detection but also&nbsp;drive meaningful transformation in lung cancer surveillance."

“Chest X-ray AI presents a valuable opportunity to cast a wider net, to identify suspected malignant pulmonary nodules ranging from 6 to 30mm in size. This can boost the fight against lung cancer and improve outcomes for patients,”&nbsp;states Samir Shah MD, Chief Medical Officer at Qure.ai. “We look forward to working closely with&nbsp;University Hospitals Cleveland Medical Center.”

large_image (17).webp

medium_image (17).webp

small_image (17).webp

thumbnail_image (17).webp

image (17).webp

UH Cleveland Activates AI for Early Lung Cancer Detection

AstraZeneca presented new data today at the European Lung Cancer Congress (ELCC) 2025, demonstrating the potential of artificial intelligence (AI) in improving lung cancer risk detection, especially within resource-limited healthcare settings. The CREATE study utilised Qure.ai’s qXR-LNMS tool to provide real-world data demonstrating its effectiveness to predict the risk of malignancy of Incidental Pulmonary Nodules on a chest X-ray compared to a radiologist’s assessment using the gold standard imaging modality, low dose CT scan. Separately, the CREATE Budget Impact Model illustrates that integrating qXR® into a clinical workflow could be cost-neutral by year 5, specifically utilising Vietnam as the model country.

These findings suggest that AI-integrated CXR could be used as a preliminary step before LDCT in resource-limited settings, to identify individuals at the highest risk and optimise the cost-effectiveness of screening programs.&nbsp;

Lung cancer is the leading cause of cancer-related deaths worldwide, it is the leading cause of cancer related death. Low-dose computed tomography (LDCT) is the gold standard for lung cancer screening, but its cost and accessibility limit its use in many countries. Chest X-rays (CXR), a helpful preliminary step to LDCT, are the most common, affordable and easily assessable triaging tool in resource-limited settings.&nbsp;

“To transform patient care and eliminate cancer as a cause of death, we must address the significant and disproportionate burden in low-and-middle-income countries and resource-limited settings via tailored and scalable solutions,” said Iskra Reic, Executive Vice President (EVP), International, AstraZeneca.&nbsp;&nbsp;

“At Qure.ai, we harness AI to transform routine chest X-rays—especially in resource-limited settings—into an opportunity for earlier lung cancer detection,” said Prashant Warier, CEO and Founder, Qure.ai. “We’re proud to support AstraZeneca’s efforts to enable a more timely diagnosis of lung cancer.”&nbsp;

The CREATE study, conducted in five countries – Egypt, India, Indonesia, Mexico, and Turkey – involved over 700 individuals and assessed qXR®'s ability to predict the risk of ‘incidental pulmonary nodules’ (IPNs) on CXR being benign or malignant.&nbsp;&nbsp;

CREATE achieved its primary outcome, demonstrating that qXR® correctly categorises IPNs on CXR as high- and low-risk of malignancy compared with radiologist assessment of LDCT. The positive predictive value (PPV) of qXR® was 54.1%, achieving the pre-defined threshold of success of 20%. The negative predictive value (NPV) was 93.5%, achieving the pre-defined threshold of 70%.&nbsp;

The results remained consistent across diverse patient groups, including people who have never smoked and individuals under 55 years old, who are typically not eligible to participate in traditional lung cancer screening programs.&nbsp;

CREATE Budget Impact Model highlights&nbsp;

A CREATE Budget Impact Model study assessed the clinical and financial implications of implementing qXR® for lung nodule detection across the entire population of Vietnam. The model predicted that qXR® implementation would lead to 3,155 additional lung cancer diagnoses (at an early stage, when curative treatment is possible) and help prevent 4,742 premature deaths over five years.&nbsp;&nbsp;&nbsp;

The study concluded that by year five, the implementation of qXR® in Vietnam could reduce premature deaths significantly and achieve cost-neutrality, as earlier cancer detection leads to more efficient treatment and reduced overall healthcare expenses.&nbsp;

AstraZeneca partners with Qure.ai to explore the utility of AI solutions to improve early-stage disease detection.&nbsp;&nbsp;

large_Group 1410090795.webp

medium_Group 1410090795.webp

small_Group 1410090795.webp

thumbnail_Group 1410090795.webp

Group 1410090795.webp

AI-Driven Chest X-Ray Tool Boosts Lung Cancer Detection

The new Health Technology Assessment (HTA) conducted by the Indian Institute of Public Health Gandhinagar (IIPHG) has reinforced the financial and operational benefits of artificial intelligence (AI)-powered chest X-ray interpretation for tuberculosis (TB) screening. The study cites that qXR from Qure.ai, not only improves efficiency, but also reduces costs compared to existing clinical pathways, making it a cost-saving intervention in India’s high TB burden regions. The assessment was conducted at the behest of the Department of Health Research, operating under the Government of India. &nbsp;

The HTA study employed cost-effective analysis based on an economic model from a health system perspective to evaluate the effectiveness of AI tools in improving TB diagnosis and care. The study focused on the diagnostic accuracy and cost-effectiveness of multiple AI-assisted chest X-ray interpretation solutions. The solutions were also compared to the manual interpretation of the X-rays.&nbsp;&nbsp;

Qure.ai’s qXR outperformed in cost efficiency and was found to be the best in overall results, compared to all other CDSCO-cleared TB AI solutions in India. The findings show that AI-assisted TB screening with qXR costs less per screened case than traditional methods.&nbsp;&nbsp;

India accounts for 28% of the world’s new TB cases, with an estimated 2.8 million new cases reported in 2023. Despite aggressive screening and treatment efforts, the country faces critical challenges in early TB detection and high patient volumes.&nbsp;&nbsp;

"AI must be a catalyst in making TB screening more accessible, equitable, and efficient, especially in high-burden settings like India. The latest health economics study confirms what we’ve observed in the field: Qure.ai’s qXR is not just cost-effective, but cost-saving. For public health programs stretched for resources, this means we can reach more people with the same budget, accelerating progress toward TB elimination," said Prashant Warier, CEO and Founder, Qure.ai&nbsp;&nbsp;

It is not the first time that qXR has been positioned as an ideal solution for TB screening. It was evaluated by the WHO in YEAR, which found it to be effective even in the absence of a human reader. The solution is deployed in 2600+ sites across 67+ countries, with a strong footprint in India and many other countries TB programs.&nbsp;

With TB elimination being a national priority in India, scaling AI-driven screening solutions like qXR can free up healthcare resources, improve workflow efficiency, and ensure no patient is left behind due to diagnostic delays.

large_IMG_6841.jpg

medium_IMG_6841.jpg

small_IMG_6841.jpg

thumbnail_IMG_6841.jpg

IMG_6841.jpg

Qure.ai increases TB detection, while saving costs, shows evaluation in India

AI-powered digital health operating system, <a href="http://qure.ai/product/qureos">QureOS</a>, launched to strengthen resource-constrained health systems, improve health access in under-served populations &amp; guide tech adoption&nbsp;

“Health systems worldwide are overburdened, under-equipped and face workforce shortages, particularly in resource-constrained settings,” states Prashant Warier, Co-founder and CEO of Qure.ai. “While AI innovation continues to accelerate, adoption remains uneven, especially within Low- and Middle-Income Countries. We renew our call to action towards driving healthcare equity with the launch of <a href="http://qure.ai/product/qureos">QureOS</a>.”&nbsp;

The number of physicians per 1000 people in western nations such as Germany, the UK and USA range from 4-2, dropping to lower than 1 in Low- and Middle-Income Countries (LMICs), and plummeting further in many African and Asian nations. Now with the future of support programs at risk, there is a health equity emergency.&nbsp;

AI can be the equalizer. In tackling TB, AI has already demonstrated that disease screening can be done at a scale in remote and the most under resourced communities. It is now possible to replicate this success in multi-disease areas. &nbsp;

With a boom in global AI-innovation, <a href="http://qure.ai/product/qureos">QureOS</a> has been designed to address the barriers of trying and adopting healthcare AI in LMICs. It brings together applications from proven vendors worldwide, across various disease areas including non-communicable diseases (NCDs), infectious diseases, maternal &amp; child health, on a single platform. It will also include a specialist AI chatbot to aid clinical decision support for primary healthcare (PHC) workers. By improving access to AI-powered digitisation, PHCs can be strengthened, aiding better triage, efficient resource allocation and improved patient care.&nbsp;&nbsp;&nbsp;

Health Ministries can prioritize local needs and embrace a systematic way to test and scale quality AI solutions. Instead of scouting for solutions and setting up multiple test pilot infrastructure, <a href="http://qure.ai/product/qureos">QureOS</a> will provide a single platform approach with AI-innovation Sandbox.&nbsp;&nbsp;

“Health systems across many African countries face significant strain due to a shortage of trained personnel and limited infrastructure. A locally adapted AI-first digital health platform has the potential to bridge these gaps, delivering equitable and effective care to underserved populations,” states Okoye Chidimma Lilian, Project Coordinator, INTEGRATE TB Project at Catholic Caritas Foundation of Nigeria. “A trusted partner like Qure.ai has been pivotal in our journey. Its expertise and innovative solutions have played a crucial role in advancing our goals of health equity and improved outcomes for communities in need.”&nbsp;

“A country-specific AI operating system that validates clinical effectiveness and tests against local datasets has the potential to advance health equity and boost health system performance at primary care levels. It will ensure healthcare innovations are tailored to local needs and fosters a sustainable, forward-looking and inclusive digital roadmap,” states Debarshi Bhattacharya, Project Director at Resolve to Save Lives.&nbsp;&nbsp;

“While LMICs recognize the potential for AI to build resilient health systems, they are often overwhelmed by choice and constrained by the financial barriers for testing,” adds Prashant Warier, Co-founder and CEO of Qure.ai. “<a href="http://qure.ai/product/qureos">QureOS</a> aims to address these hurdles, and we are rapidly moving towards deployment in nations in Africa and Asia facing severe health inequalities.”&nbsp;&nbsp;

Founded in 2016, Qure.ai is committed to making healthcare more accessible and equitable globally, with deployments in more than 90 countries.&nbsp;&nbsp;&nbsp; For more information about&nbsp;how&nbsp;QureOS can discover, test and deploy AI in your country's healthcare ecosystem, please click here&nbsp;<a href="http://qure.ai/product/qureos">qure.ai/product/qureos</a>&nbsp;

large_PR thumbnail.webp

medium_PR thumbnail.webp

small_PR thumbnail.webp

thumbnail_PR thumbnail.webp

PR thumbnail.webp

Answering The LMIC Health Equity Emergency

Prayagraj, 20th February 2025 — Qure.ai’s artificial intelligence (AI)-enabled chest X-ray interpretation solution, qXR, is now live at the Maha Kumbh Mela 2025. Deployed at the Central Hospital in Sector 2, the biggest medical facility set up for addressing the immediate medical requirements of the pilgrims, the qXR software is being used for quick triaging coupled with TB surveillance. Through incidental screening, the AI solution can automatically flag potential TB cases among individuals undergoing chest X-rays for any reason. &nbsp;

Since its deployment, the AI solution has analysed the chest X-rays done at the hospital and flagged 36.22% as abnormal, with 12% of those showing presumptive signs of TB. This proactive approach is expected to help identify hundreds of TB cases, incidentally, over the course of the event, aligning with the Government of India’s 100-Day TB Challenge and its ambitious goal of eliminating TB by 2025.&nbsp;

The Maha Kumbh Mela, recognized as the world’s largest congregation, presents unique public health challenges. With an estimated 50 crore attendees over six weeks, the scale of healthcare delivery required is unparalleled. The deployment of AI for real-time screening at a mass gathering of this magnitude highlights the potential for technology-driven solutions to strengthen large-scale disease surveillance and early intervention.&nbsp;

Commenting on the initiative, Dr Arun Kumar Tiwari, Chief Medical Officer, Prayagraj, said: "The AI system has provided timely and reliable support in our TB screening efforts. Given the high volume of patients at the Kumbh, the technology has significantly enhanced our ability to prioritize individuals who need further diagnostic evaluation and treatment. This is the first time AI is being used for TB surveillance at a mass gathering of this scale through an incidental screening model. "In a gathering like the Kumbh, AI ensures every chest X-ray is screened for TB, enabling early intervention and breaking the chain of transmission”, he added.&nbsp;

Prashant Warier, CEO and Co-founder of Qure.ai, added: "Mass gatherings like the Maha Kumbh present both an opportunity and a responsibility for public health interventions. Just as surveillance cameras are being used for crowd management and security, AI-driven solutions like qXR are ensuring that healthcare keeps pace with the scale and complexity of the event. The deployment of qXR at the Maha Kumbh is not merely a technology showcase—it’s a scalable model for large-scale TB surveillance. It offers a blueprint for state governments to strengthen their public health systems by incorporating AI for real-time, community-based TB screening, especially in high-risk, high-density settings."&nbsp;

The deployment at Maha Kumbh Mela offers a replicable framework for large-scale TB screening programs in other mass gatherings, high-risk communities, and densely populated urban areas.&nbsp;&nbsp;

Integrating AI into TB programs can:&nbsp;

Dr. Manoj Kaushik, Chief Medical Secretary, Central Hospital, Prayagraj, noted:&nbsp;"We are committed to leveraging technology to improve public health outcomes. The integration of AI in TB screening at the Maha Kumbh Mela is a step forward in our efforts to enhance disease surveillance and ensure timely care for all."&nbsp;

India bears the world’s highest burden of tuberculosis, and early diagnosis remains a critical factor in controlling the disease’s spread. Events like the Maha Kumbh demonstrate that innovative approaches can improve healthcare access at scale. As the country moves toward its goal of eliminating TB by 2025, AI-driven solutions like qXR&nbsp; ffer a way to strengthen detection and diagnosis, particularly in resource-limited and high-density environments.&nbsp;

large_IMG_5268.jpg

medium_IMG_5268.jpg

small_IMG_5268.jpg

thumbnail_IMG_5268.jpg

IMG_5268.jpg

Qure.ai’s AI-Powered TB Screening Supports Public Health Efforts at Maha Kumbh Mela 2025

ZQSI retrospective review showed 98% of patients predicted by AI were truly eligible for MT procedure, reducing the need for advanced imaging &amp; saving time

A new retrospective study presented by Qure.ai at the World Stroke Congress 2024 in Abu Dhabi showcases the potential of artificial intelligence (AI) to expedite the eligibility assessment for Mechanical Thrombectomy (MT) in patients suffering from Acute Ischemic Stroke (AIS).  &nbsp;

The findings offer the potential to help healthcare providers expedite care, decrease the door to puncture time and lessen the cost burden stemming from advanced imaging, especially in low-income settings. This could be a game changer with World Stroke Organization predictions of stroke burden standing at <a href="https://www.world-stroke.org/assets/downloads/WSO_Annual_Report_2023_online.pdf" target="_blank">87% in low- and middle-income countries (LMICs) by 2050</a>.    &nbsp;

The study was conducted on a retrospective cohort of 260 patients that underwent treatment for stroke at Zeenat Qureshi Stroke Institutes (ZQSI), Minnesota, USA. Using the Qure.ai AI enabled stroke detection solution qER, the eligibility of each patient was analysed for a Mechanical Thrombectomy using ASPECT Score, infarct volume, and a few clinical parameters. The data was split into two equal halves, allowing for customised testing parameters. The first set (Model 1) was analysed using factors like National Institutes of Health Stroke Scale (NIHSS), Infarct volume, ASPECT score, time since the onset of symptoms and patient age to predict the eligibility for MT. The second set (Model 2) was analysed on the same parameters but added the presence of large vessel Occlusion (LVO). About 82.5% of the patients predicted as eligible for MT by the first model had undergone MT while 97.5% of the patients predicted as eligible for MT by Model 2 had undergone MT.

“The rising global stroke burden demands immediate action, and digital health innovation plays a crucial role in optimizing care. This study at ZQSI shows that Qure.ai’s AI models can help support physicians assess mechanical thrombectomy eligibility with greater speed and precision, addressing one of the most time-sensitive aspects of stroke treatment. We are confident that these solutions will significantly enhance stroke care globally and help in alleviating stroke burden, especially for LMICs,”&nbsp;said&nbsp;Prashant Warier, Founder and CEO, qure.ai.

image.png

“This AI-driven approach represents a breakthrough in stroke care, streamlining the process of determining treatment eligibility and reducing dependence on advanced imaging. By leveraging AI's capabilities, we can accelerate clinical decision-making, optimize patient outcomes, and demonstrate the transformative potential of technology led healthcare.” Said Adnan I. Qureshi, Professor of Neurology and Program Director Endovascular Surgical Neuroradiology program, University of Missouri, Columbia, and Chief Executive Officer, ZQSI.

Qure.ai’s Stroke Care Suite includes qER AI solution and Qure App.  qER, an advanced deep-learning software that assesses NCCT scans to identify intracranial haemorrhages, infarcts and Large Vessel Occlusion on CT Angiography. The AI algorithm can also provide anatomical location identification and quantification, and ASPECTS scoring for Stroke severity. It offers a priority flag for critical cases, an overlay highlighting abnormal findings, and detailed reports quantifying abnormalities. qER is FDA, CE MDR cleared, with approval from multiple national regulators. The Qure App facilitates critical care coordination with timely alerts.  &nbsp;

Stroke is the <a href="https://www.world-stroke.org/assets/downloads/WSO_Annual_Report_2023_online.pdf" target="_blank">second-leading cause of death in the world</a>. Each year there are 12 million new cases, translating to 143 million healthy years of life lost to stroke per year. It is estimated that 1in 4 people over the age of 25 will experience stroke in their lifetime.

Note: Abstract Number: SO028 / #1302

large_WSC-02 (1)-2-2.jpg

medium_WSC-02 (1)-2-2.jpg

small_WSC-02 (1)-2-2.jpg

thumbnail_WSC-02 (1)-2-2.jpg

WSC-02 (1)-2-2.jpg

New study highlights potential of AI to determine swift mechanical thrombectomy eligibility in stroke patients  

Jim Mercadante brings 25 years of experience in AI, medical devices &amp; med-tech to steer ongoing momentum&nbsp;

New York, January 9, 2025: The world’s most adopted healthcare AI company, <a href="https://www.qure.ai/" target="_blank">Qure.ai</a>, has appointed a new Chief Commercial Officer to oversee and expand global sales and business development strategy. Based in New York, Jim Mercadante joins a growing commercial and operations team to consolidate growing momentum and orchestrate further success.&nbsp;&nbsp;&nbsp;

With an AI deployment footprint in more than 90 countries, Qure.ai has seen exponential growth in Asia, Africa, the Middle East and Europe over the last 8 years, with demand for its healthcare AI and digital health tools now growing in North and South America.&nbsp;&nbsp;

Jim Mercadante brings a wealth of commercial leadership, sales, business growth and strategic marketing experience with leadership positions at Abbott, Johnson and Johnson, GE, Terumo and most recently Rapid AI. His leadership will be instrumental as Qure.ai builds on the impetus created by its recent Series D funding, which will drive growth across the US and other geographies, support ongoing innovation in AI and digital health solutions, and explore complementary acquisitions.&nbsp;

Prashant Warier, Co-Founder and CEO of Qure.ai states, “We warmly welcome Jim Mercadante and look forward to his leadership to advance our global sales strategy, strengthen partnerships with healthcare providers and channel partners, plus optimize commercial operations for growth globally. He will be based in our USA office but travel extensively to advance our worldwide sales strategy, consolidate existing customer successes and optimise commercial operations.”&nbsp;

Jim Mercadante, Chief Commercial Officer of Qure.ai states, "Qure.ai stands out for its exceptional people, cutting-edge technology, and clear vision for the future of healthcare. I’m excited to contribute to the company’s growth as we continue to expand globally and develop AI solutions that address critical healthcare challenges."

large_Jim Mercadantes joins qure-01.webp

medium_Jim Mercadantes joins qure-01.webp

small_Jim Mercadantes joins qure-01.webp

thumbnail_Jim Mercadantes joins qure-01.webp

Jim Mercadantes joins qure-01.webp

Qure.ai appoints USA based Chief Commercial Officer to further global expansion strategy 

100,000 patient chest X-rays to be proactively reviewed over the next year for incidental pulmonary nodules and cases tracked for follow-up&nbsp;

<a href="https://www.erasmusmc.nl/en/" target="_blank">Erasmus Medical Centre (MC),</a> one of the largest and most authoritative scientific university medical centres in Europe, has extended its long-term collaboration with global innovator <a href="https://www.qure.ai/" target="_blank">Qure.ai</a>, by commencing an innovative Chest X-ray AI study. It aims to detect and follow-up Incidental Pulmonary Nodules (IPN) using state-of-the-art AI and digital healthcare coordination tools.&nbsp;&nbsp;

The CE-certified and FDA cleared Chest X-ray AI solution, <a href="https://www.qure.ai/product/lung-nodule-management" target="_blank">qXR</a>, has now gone live integrating into Erasmus MC’s existing radiology workflow. qXR automatically reviews patient Chest X-rays requested from multiple settings in the hospital environment including the Emergency Department, Outpatients and wider clinical specialties of Cardiology or Pulmonology. The AI provides a second set of eyes to radiologists, flagging the presence of lung nodules that require further investigation. The collaboration also includes the use of Qure’s new lung nodule management platform, <a href="https://www.qure.ai/product/lung-nodule-management" target="_blank">qTrack</a> to coordinate patient cases through smart prompts and custom notifications. Together, the aim is to detect lung cancer early and improve patient life outcomes.&nbsp;&nbsp;

News and Press