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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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Partnership between North East London Cancer Alliance and Qure.ai improves chest X-ray reporting&nbsp;

North East London Cancer Alliance is reporting early success from its partnership with Qure.ai, following the rollout of artificial intelligence (AI) delivered through Sectra Amplifier Services to support lung cancer diagnosis across the region.&nbsp;

The introduction of Qure.ai’s chest X-ray tool, qXR, is delivering faster reporting and greater accuracy in identifying critical cases. At Barts Health, turnaround times for the most urgent chest X-rays have improved by 61.5%, reduced from 13 days to 5. Reporting times for urgent cancer cases have improved by 41.7%, dropping from 12 days to 7. The Alliance is now working towards a consistent &lt;3-day turnaround for all chest X-ray reports.&nbsp;

The improvements come at a time when radiology services are under sustained pressure. Across north east London, demand for chest X-rays rose by 94% between 2017 and 2022, increasing from 139,080 requests to around 270,000. At the same time, a 29% national shortfall in radiologists has placed significant strain on services, with some patients waiting up to 21 days for results.&nbsp;&nbsp;

Wayne Douglas, Programme Lead at North East London Cancer Alliance, said: “The early results from using AI in chest X-rays are encouraging. By embedding AI into our lung cancer pathway, we are beginning to reduce reporting delays, improve prioritisation, and provide greater assurance for patients and clinicians. This work is an important step in strengthening diagnostic capacity across North East London.”&nbsp;

Clinical teams across participating Trusts have provided positive feedback, with training underway to ensure junior doctors and radiographers are able to use the AI effectively.&nbsp;&nbsp;

The success to date reflects collaboration across the Alliance and its partners. Established in 2020 under NHS England’s Cancer Alliance programme, North East London Cancer Alliance works with providers, commissioners and community partners across eight boroughs, serving a population of 3 million through Barts Health NHS Trust, Barking, Havering and Redbridge University Hospitals NHS Trust, and Homerton Healthcare NHS Foundation Trust.&nbsp;

Bhargava Reddy, Chief Business Officer, Oncology at Qure.ai said: “These early results show how AI can play a supportive role in diagnostic pathways. Working with North East London Cancer Alliance and Sectra, we are seeing measurable improvements in reporting times and greater confidence in identifying urgent cases.”&nbsp;

A two-year evaluation is underway, with early findings already shared with NHS England. The programme will continue to track wider impacts, including time to CT and time to diagnosis, with future plans to extend AI integration into CT scanning.

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AI Speeds Up Lung Cancer Detection in North East London 

Findings presented at ESMO 2025 reveal how AI analyzing routine chest X-rays helps detect early-stage lung cancer in patients who fall outside traditional screening guidelines&nbsp;

An artificial intelligence (AI) tool analyzing everyday chest X-rays has shown remarkable promise in spotting early-stage lung cancer, even among people who have never smoked or are younger than traditional screening age. The findings, presented at the European Society for Medical Oncology (ESMO) Congress 2025, point to how technology could help close long-standing gaps in lung cancer detection.&nbsp;&nbsp;

The study was jointly led by&nbsp;<a href="https://www.qure.ai/" target="_blank">Qure.ai</a>&nbsp;and AstraZeneca. It demonstrates the growing role of AI in expanding access to early detection, particularly in regions where CT-based screening programs are limited or unavailable.&nbsp;

The CREATE study, conducted across five countries – Egypt, India, Indonesia, Mexico and Turkey - evaluated Qure’s AI-driven Lung Nodule Malignancy Score (qXR-LNMS) that analyzes routine chest X-rays or high and low risk individuals and flags nodules at high risk of malignancy.&nbsp;

Out of more than 700 participants, qXR correctly identified 96% of confirmed lung cancer cases, including nearly 60% among people who had never smoked, and&nbsp;some&nbsp;under the age of 50. Remarkably, 46% of these cases were caught at early stages (I–III), when treatment outcomes are most favourable.&nbsp;

The CREATE study builds on the success of its first phase, which validated the model’s accuracy against CT findings. With this next stage, the longitudinal tracking of patients provides critical real-world evidence of how qXR can guide ongoing management and follow-up beyond the first point of detection.&nbsp;

“These results show how AI can transform the way we find and follow up on potential lung cancers,” said Sagar Sen, Head of Global Life Sciences and Strategic Alliances at Qure.ai.&nbsp;“By flagging high-risk nodules, qXR helps clinicians triage chest X-rays more effectively to detect disease incidentally and earlier. This ensures timely follow-up. It’s an approach that brings precision to everyday practice.”&nbsp;

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AI Uncovers Lung Cancer Risk in Younger, Non-Smoking Individuals, CREATE Study Finds

Qure.ai has forged a commercial partnership with the USARAD Holdings Inc. (USARAD), demonstrating its commitment to enhancing radiological decision-making.&nbsp;

The three-year partnership will focus on the deployment of Qure’s chest X-ray AI software, “qXR.” The solution provides an analysis of chest X-rays, enabling radiologists to make swift decisions, ensure effective resource allocation, and prioritize critical cases by highlighting key clinical markers.&nbsp;

USARAD is actively adopting AI technologies to enhance reporting efficiency and bolster diagnostic precision, aiming to improve patient outcomes and drive value. The partnership validates Qure’s goal to partner with leading organizations that are at the forefront of embracing AI technology to augment healthcare delivery and optimize legacy pathways. It is also a testament to Qure's growing presence in the U.S. healthcare market, along with its dedication to improving patient outcomes through technology.&nbsp;

Commenting on the partnership, Prashant Warier, Co-founder and CEO of Qure.ai, said "We are thrilled to embark on this transformative journey into the US Teleradiology Market alongside USARAD. This partnership underlines Qure.ai's unwavering commitment to revolutionizing radiological decision-making through AI innovation. Our qXR software's deployment will empower radiologists with swift, insightful chest X-ray analyses, facilitating prioritization of critical cases and efficient resource allocation. Together with USARAD, we are shaping the future of healthcare delivery and reaffirming our dedication to optimizing patient outcomes through cutting-edge technology."&nbsp;

USARAD, a Nanox subsidiary, is a U.S.-based teleradiology company with over 116 U.S. certified radiologists in its network, that was formed by a collaborative effort of American radiologists, all Board Certified by the American Board of Radiology, recognizing the need for high-quality, reliable on-call and daytime radiology and teleradiology services,&nbsp;

“This partnership signifies an exciting leap toward redefining patient care through AI-driven solutions,” stated Dr. Michael Yuz, CEO and founder of USARAD. “With qXR at the forefront, we are not just embracing innovation; we're reshaping how radiologists’ approach critical decision-making, ultimately leading to better outcomes and more efficient resource utilization. This collaboration reflects our shared commitment to driving progress in healthcare delivery and underscores the potential of AI to elevate the standards of patient-centric care.”&nbsp;

As a recognized leader in teleradiology solutions in the U.S., USARAD's ethos aligns seamlessly with Qure's growth aspirations. The integration of qXR is set to augment USARAD's diagnostic efficiency, paving the way for potential cost reductions, along with swifter and more accurate radiological decisions.&nbsp;&nbsp;&nbsp;

In the rapidly evolving healthcare tech sphere, Qure’s alliance with USARAD positions both companies at the vanguard of teleradiology, propelling innovative solutions for superior patient care.

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Qure.ai Expands U.S. Teleradiology Market Presence with New USARAD Partnership

The paper summarises the results of a retrospective study of the comparative assessment of Chest X-ray interpretations by Qure.ai’s AI-enabled Chest X-ray solution in comparison to a radiologist and pulmonologist in predicting the clinical status of patients with COVID-19-induced pneumonia.

Dubai, 18 September 2023 – New research published in the Journal of Advances in Radiology and Medical Imaging, underscores the remarkable potential of artificial intelligence (AI) in aiding the diagnosis of COVID-19-induced pneumonia. The study compares the precision of AI-powered chest X-ray interpretations against human clinical expertise. &nbsp;

Pneumonia is a prevalent and severe respiratory disorder with the potential for irreversible lung damage and significant mortality. The timely and accurate diagnosis of the disease is paramount. Chest radiography has long been the gold standard to assess the clinical condition and progress of patients with respiratory disorders, including pneumonia. &nbsp;

This study, led by Consultant Radiologist Usama Al Bastaki and his colleagues, puts into focus Qure.ai's Chest X-ray Algorithm (qXR). The aim was to measure the algorithm's quantitative evaluation against the qualitative judgements of senior radiologists and pulmonologists. The algorithm can identify various radiological findings, including opacities, consolidation, pleural effusions, and more. &nbsp;

Over 535 chest X-rays from 100 COVID-19 pneumonia-afflicted patients were meticulously scrutinized. Each patient was chosen based on having at least one subsequent chest X-ray, which facilitates tracking the evolution of the disease. An important aspect of this research was comparing the AI’s interpretations to human expert conclusions and the ability of the software to predict the trajectory of the disease via multiple assessments of patient health. &nbsp;

“From this research, we know that AI-enhanced diagnostics can expedite the detection of conditions, including critical ones like pneumonia, enabling faster treatment and ultimately saving lives in our hospitals,” said radiologist and lead researcher Dr. Usama Al Bastaki.&nbsp;

“It’s encouraging to see research publications like this validating our belief that AI has the potential to enhance diagnostic precision, prioritize critical cases, and in the future also provide prognostic risk assessment”, said Preetham Putha, Chief AI Officer, Qure.ai.&nbsp;&nbsp;

Key Findings Include: &nbsp; &nbsp;

AI and Radiologist Agreement: The study found a high level of agreement between AI-based interpretations and radiologists, even when clinical data was not provided to the radiologists during assessment. &nbsp;

Predictive Accuracy: The AI-based qXR algorithm demonstrated precise and consistent agreement with radiologists, particularly in cases of patients with deteriorating clinical status. &nbsp;

Subgroup Consistency: The agreement between AI and radiologists remained consistent across different patient characteristics, indicating the robustness of the AI model. &nbsp;

Interestingly, even without access to patients’ clinical data, radiologists' assessments resonated closely with the AI's readings, indicating a lack of bias in their evaluations. &nbsp;

Results from this study suggest that the qXR algorithm by Qure.ai could be instrumental in diagnosing and monitoring Covid-19 pneumonia progression, particularly when there is limited access to radiologists or when they are inundated with cases. The inference is clear: AI has the potential to refine diagnostic accuracy, mitigate errors, and prioritize acute cases in emergency settings. &nbsp;

As we navigate the landscape of modern medicine, this research offers a tantalizing glimpse into an AI-integrated future in radiology, emphasizing its potential to amplify patient care quality and outcomes. Seamlessly integrating AI solutions into clinical workflows can standardize reporting, minimize errors, and prioritize critical cases.  &nbsp;

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AI powered diagnostic systems show promise in predicting the clinical status of patients with COVID-19-induced pneumonia

Potential to lighten consultant radiologists’ burden by up to 58% through radiographer reporting&nbsp;

Frimley Health NHS Foundation Trust and Qure.ai have announced the early results of&nbsp;a pilot study&nbsp;using an innovative radiology AI solution to read and differentiate between normal and abnormal chest X-rays (CXRs).&nbsp;&nbsp;

<a href="https://qure.ai/product/qxr/" target="_blank">qXR, a CE class IIb MDR</a>&nbsp;cleared solution developed by Qure, was deployed with the hypothesis to categorise normal x-rays – approximately 40% of the caseload from GP and outpatient requests – and augment overall reporting efficiency. The aim of the study was to highlight AI’s potential role in optimising radiology department workflows, to boost efficiency and enhance patient outcomes.&nbsp;&nbsp;

Early results show 99.7% accuracy in triaging CXRs as normal, with the potential to reduce consultant radiologist’s workload by up to 58% by transferring cases to radiographer reporting workload. This could save consultant radiologists up to 2 hours per day, freeing up time to concentrate on specialist and complex imaging reports.&nbsp;

Additionally,&nbsp;<a href="https://qure.ai/product/qxr/" target="_blank">the qXR AI</a>&nbsp;identified all cancer cases, including inconspicuous cancer risk nodules that may traditionally remain unnoticed. This heralds the potential of using AI for early detection and treatment of lung cancer.&nbsp;&nbsp;

Dr Amrita Kumar, Consultant Radiologist and AI Clinical Lead at Frimley Health NHS Foundation Trust states, “AI offers a transformative advantage to Frimley Health NHS Foundation Trust, enabling efficient triage of normal chest X-rays and empowering radiologists to focus on complex cases. By optimising efficiency, Qure’s qXR Chest X-ray solution contributes to better patient outcomes and addresses the critical need for innovative AI solutions in the radiology department.”&nbsp;

Darren Stephens, Senior Vice President &amp; Commercial Head UK and Europe of Qure.ai comments, “The ongoing radiologist shortage, now estimated by Royal College of Radiologists to be 40% by 2027, underscores the importance of healthcare AI to help augment the precious human resource that currently exists, and ensure the delivery of the highest standard of patient care into the future. The qXR study at&nbsp;Frimley Health NHS Foundation Trust&nbsp;is testimony to the clinical leadership at the Trust in embracing AI as an opportunity for positive change.”&nbsp;&nbsp;

Channel Partners:&nbsp;Philips, EPIC

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Early findings of AI study at Frimley Health NHS Foundation Trust show 99.7% accuracy in triaging chest X-rays as normal

Qure.ai’s&nbsp;<a href="https://qure.ai/product/qxr/" target="_blank">qXR software</a>&nbsp;procured though the NHS Shared Business Services (NHS SBS) Framework Agreement

Clinicians at East Kent Hospitals are using artificial intelligence (AI) software to help check chest x-rays for patients in its emergency departments.

The qXR software, developed by Qure.ai, can spot potential issues almost instantly and alert doctors, reducing any potential delay to starting treatment.

It means issues such as cancer, collapsed lungs and&nbsp;tuberculosis&nbsp;can potentially be detected quickly, without having to wait for a radiologist or expert reporting radiographer to review the images.

Dr Neelan Das, consultant interventional radiologist, and AI lead for the Trust, said there were clear benefits for patients and emergency department staff at the William Harvey Hospital in Ashford and Queen Elizabeth The Queen Mother Hospital in Margate. He said: “We are very excited about this new imaging innovation which we think will make a real difference to the departments. The technology allows for faster interpretation and targeted reporting of the images so that any abnormalities can be flagged immediately for the doctor to review. Our initial testing has shown that it is at least as sensitive as a senior radiologist and when it is rolled out fully across our emergency departments it could analyse thousands of x-rays every month.”

It is the latest AI project brought in by the Trust, which has already used other software to help monitor patients’ eye health and detect signs of disease, detect evidence of stroke, and analyse potential&nbsp;lung cancers on CT scans&nbsp;as part of the new national lung cancer screening programme.

East Kent Hospitals is part of the National Institute for Health and Care Research’s AI Centre consortium – a group of 16 organisations working on ways to include the technology to benefit NHS patients.

Qure’s qXR software was procured via the&nbsp;<a href="https://www.sbs.nhs.uk/fas-artificial-intelligence-radiotherapy" target="_blank">NHS SBS ‘Provision of AI, Imaging &amp; Radiotherapy Equipment, Associated Products and Diagnostic Imaging’ Framework Agreement.</a>

Emergency department doctors will review the findings generated by the software before deciding on any treatment, and senior radiologists will regularly check the reports to ensure accuracy. The qXR AI solution will highlight critical cases, allowing doctors to focus on people who need the most urgent treatment.

Dr Das said: “It is not about replacing medical staff, and we are very clear that the AI-generated report is guidance for our clinicians who will make the final decision on whether they agree with it or not, and will plan any treatment they deem necessary. But it has real potential to improve patient care and outcomes and to reduce delays in our emergency departments. Ongoing performance monitoring of all new AI technologies introduced into the NHS is key to success and adoption.”

Darren Stephens, SVP and commercial head – UK and Europe for Qure.ai, said: “This is a significant milestone for Qure.ai’s solution to be procured though the NHS SBS Framework Agreement. We are excited to partner with East Kent Hospitals with the aim of powering the efficiency of radiology reporting of chest X-rays with very high accuracy. A layer of AI-enabled chest X-ray triaging can prompt precise identification of critical cases, resulting in optimised resources and enhanced patient experiences."

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AI software helps speed up x-ray reporting: Qure.ai partners with NHS East Kent

<a href="https://www.inhealthgroup.com/" target="_blank">InHealth</a>, the UK’s largest specialist provider of diagnostic and healthcare solutions, has announced a partnership with&nbsp;<a href="http://qure.ai/" target="_blank">Qure.ai</a>, a market leader in medical artificial intelligence (AI) solutions. Through this partnership, InHealth will be deploying&nbsp;<a href="http://qure.ai/" target="_blank">Qure.ai</a>‘s AI solution to aid in the classification of chest X-rays into conventional and unconventional exams. The solution will be deployed across InHealth’s entire Tele-reporting service arm to help enhance the quality and accuracy of reporting using AI.

Jonny McDaniell, Director of Operations – Reporting at InHealth, said: “We are excited to be partnering with&nbsp;<a href="http://qure.ai/" target="_blank">Qure.ai</a>&nbsp;to deploy&nbsp;<a href="https://www.qure.ai/product/qxr/" target="_blank">qXR AI software</a>&nbsp;into our tele-radiology platform to assist physicians in highlighting life-threatening health markers and improve reporting time for critical cases.”

<a href="http://qure.ai/" target="_blank">Qure.ai</a>‘s EU MDR CE Class IIb – certified chest X-ray solution, qXR, will help identify which cases are clear of clinically relevant findings, enabling radiologists to read them more accurately within minutes. With Qure’s qXR in place, InHealth is pleased to be driving efficiency and quality in its reads, enabling them to better support clients in tackling chest X-ray (CXR) backlog challenge. It will also help InHealth to prioritise more clinically urgent cases.

Speaking about the partnership,&nbsp;<a href="https://www.qure.ai/about-us/" target="_blank">Darren Stephens, Senior Vice President &amp; Commercial Head UK and Europe of</a>&nbsp;<a href="http://qure.ai/" target="_blank">Qure.ai</a>, said, “Our partnership with InHealth is a validation to our dominance in the UK radiology AI market. By combining our expertise in medical imaging with InHealth’s commitment to delivering high-quality diagnostic services, we can make a significant impact on patient outcomes. Together, we can advance the frontiers of healthcare and improve the lives of people across the UK.”

<a href="http://qure.ai/" target="_blank">Qure.ai</a>‘s chest X-ray software can detect multiple lung markers in under one minute. It can accurately assess radiological findings presumptive of a host of lung diseases, including lung cancer, pneumonia, COPD, TB, and heart failure, among others.

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InHealth partners with Qure.ai to enhance quality of Telereporting services with AI-powered chest X-ray solution

Qure.ai is proud to announce a significant milestone in our journey to transform radiological practices through artificial intelligence. Our AI-driven medical imaging software has achieved the CE Class IIb certification under the European Union Medical Device Regulation (EU-MDR). This notable certification highlights our adherence to the highest standards of safety, performance, and quality in the European Union, extending our reach across 31 countries.

Our portfolio, now among the most comprehensive in the EU, employs AI to detect a range of abnormalities in various radiological modalities, including Chest X-rays, Chest CT, Head CT, and Musculoskeletal X-rays. This advanced AI software is designed to support radiologists in diverse healthcare environments, enhancing their ability to interpret scans accurately and efficiently.

Prashant Warier, our Co-founder and CEO, emphasizes the significance of this achievement: "Attaining the EU MDR certification is not only a reflection of our commitment to product excellence but also a reinforcement of our global presence as a reliable AI software provider. This milestone is a testament to the rigorous validation our products have undergone, marking their deployment in over 1000 sites worldwide across more than 75 countries. The certification paves the way for expanding our influence in the EU market, aiming to improve patient outcomes with our state-of-the-art imaging AI solutions."

The EU MDR certification process is known for its stringency and thoroughness, ensuring medical devices meet the highest standards of safety and efficacy. Our products have been validated in 71 countries, demonstrating our global commitment to quality.

In collaboration with Erasmus MC, we have launched the AI Innovation Centre for Medical Imaging, a groundbreaking initiative to evaluate and enhance the robustness and impact of our AI solutions on patient outcomes. Dr. Jacob J. Visser, a radiologist and chief medical information officer at Erasmus MC, outlines the center's objective to rigorously assess the performance of our AI solutions in diverse patient cohorts, thereby solidifying their role in clinical decision-making and specific disease workflows like lung cancer, ER, and stroke.

The MDR certification is a significant acknowledgment of the safety and efficacy of our AI software, affirming its compliance with EU medical device regulations. This assures healthcare professionals and patients alike of our software's extensive evaluation and reliability in the global market.

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Qure.ai Awarded EU MDR Certification for Its AI solutions

Qure.ai has exciting news - our groundbreaking chest X-ray AI product, qXR, has now been successfully integrated with Fujifilm's AI-enabled platform, REiLI®. This innovative fusion was demonstrated at the latest Radiological Society of North America (RSNA) event, showcasing the full potential of this collaboration in improving diagnostic solutions.

This partnership marries Qure's commitment to making care accessible, affordable, and timely across the globe with Fujifilm's aim of improving patient outcomes.

FUJIFILM Healthcare Americas Corporation, a pioneer in diagnostic imaging and medical informatics solutions, presents an ideal collaborator for Qure. From launching the X-ray film in 1936 to building a comprehensive healthcare portfolio, Fujifilm has consistently evolved to meet the changing healthcare landscape.

Fujifilm's dedication to progress in AI diagnostics is evident through REiLI®, a platform that masterfully blends its image-processing technologies with AI. This open platform enhances the existing diagnostic imaging experience, offering even more depth to their work in digital radiography, endoscopy, and in-vitro diagnostics.

Our qXR software, a CE class II certified deep learning technology, identifies and highlights health markers in chest radiographs, providing clinically relevant tags. It complements Fujifilm's Synapse PACS, part of the AI-enabled REiLI® platform. 

This combination facilitates the extensive integration of Qure's algorithms, prioritizing scans, flagging results, and enabling immediate reporting of critical cases.

Qure and Fujifilm share a history of successful collaboration, applying qXR in Fujifilm's&nbsp;<a target="_blank" href="https://www.fujifilm.com/products/medical/digital_radiography/fdr_nano/">mobile&nbsp;</a>and&nbsp;<a target="_blank" href="https://www.fujifilm.com/products/medical/digital_radiography/fdr_xair/">portable&nbsp;</a>X-ray devices. qXR has shown its prowess in detecting TB, COVID-19, lung cancer, and other critical symptoms in various clinical settings worldwide. Qure, Fujifilm, and IHVN (Institute of Human Virology Nigeria) joined forces to deploy AI-embedded ultra-portable X-ray machines in rural Nigeria, screening 30,000 people for TB and identifying over 600 at-risk cases in six months.

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Furthermore, our partnership extends to the United Arab Emirates, where we have established a color-coding system within Fujifilm's Synapse Radiology Information System.

 This collaboration allowed us to screen around 1.5 million people for TB, with plans to expand into other areas like musculoskeletal (qMSK) and head CT (qER).

The convergence of technologies like Fujifilm's AI-enabled platform REiLI® and Qure's qXR is poised to transform how physicians prevent, diagnose, and treat diseases with minimal workflow changes and an enhanced AI usability experience. 

As we look ahead, we are excited to expand our partnership into new care areas and geographies, reaching out to millions of patients needing better healthcare solutions.

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Qure.ai validated on Fujifilm’s AI-enabled platform REiLI®

Harnessing the transformative power of innovation, AstraZeneca is paving the path for the future of healthcare. 

Embracing digital tools and advanced technologies, the pharmaceutical giant aims to address unmet patient needs in a post-pandemic world while ensuring that our health systems are resilient and future-proof.

AstraZeneca realizes this ambition through its A.Catalyst Network, a dynamic global collective of over 20 health innovation hubs. 

Collaborating with health tech startups, local governments, and cross-industry partners, the Network aims to address contemporary challenges, improve equitable access to healthcare, and advance scientific innovation.

A prime example of such collaboration is AstraZeneca's partnership with <a href="https://qure.ai/">Qure.ai</a>, a developer of deep learning algorithms for interpreting radiology images.

Through its tool, 'qXR,' Qure.ai has revolutionized the reading of chest X-rays, automating the detection and localization of up to 29 markers, including those indicative of potential lung cancer.

As the most commonly ordered diagnostic imaging test worldwide, chest X-rays are pivotal in lung cancer diagnosis. 

However, interpreting these images often requires significant expertise and experience, which can lead to missed or delayed diagnoses.

 Qure.ai's CE-marked qXR algorithm addresses this by offering high levels of accuracy in detecting lung nodules, thus improving sensitivity by 17% compared to traditional radiologist readings.

In collaboration with Qure.ai, the A. Catalyst Network will further explore the application of deep learning algorithms to identify patients with suspicious radiographic lung markers and facilitate their referral for a confirmed diagnosis. 

This partnership will specifically focus on overcoming barriers that limit access to diagnostic tools, aiming to support early lung cancer detection, reduce mortality rates, and improve patient outcomes, particularly in low- and middle-income countries.

In addition to their commitment to the early-stage detection of lung cancer, 

AstraZeneca has also launched the 360º vaccine Confidence Building program to improve disease awareness and education. 

With a focus on developing nations in Latin America and East Asia, this initiative harnesses digital capabilities to deliver tailored content and create a more informed understanding of COVID-19 among medical professionals and the general public.

The comprehensive program has established a framework that includes a social media strategy, a medical education program for healthcare professionals, and a digital awareness campaign utilizing bespoke educational resources to enhance communication and engagement.

 The campaign has successfully identified and engaged with more than 150 external digital experts.

AstraZeneca's innovative partnership with Qure.ai and the 360º vaccine Confidence Building campaign has been acknowledged at the Reuters Pharma Awards 2022. 

These initiatives embody the company's enduring commitment to revolutionizing healthcare, putting patients at the heart of their focus.

 As leaders in the pharmaceutical industry, AstraZeneca strives for a sustainable healthcare ecosystem, reshaping healthcare approaches better to serve people, society, and the planet, both now and in the future.

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Transforming Healthcare with Innovative Science: AstraZeneca Collaborates with Qure.ai

The COVID-19 pandemic accentuated the urgent need for health equity, a notably pronounced challenge in low- and middle-income countries (LMICs).&nbsp;

As disparities in healthcare accessibility have become glaringly apparent, multinational pharmaceutical and biopharmaceutical company AstraZeneca has made significant strides in this mission.&nbsp;

The company's commitment to boosting equitable and affordable access to treatments earned them a top ranking in the&nbsp;<a target="_blank" href="https://accesstomedicinefoundation.org/news/2022-access-to-medicine-index-more-companies-move-to-address-access-to-medicine-will-they-now-go-further">2022 Access to Medicine Index.</a>

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