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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.

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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.

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“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

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

Mumbai, India – 30th July, 2024 – Qure.ai, a global leader in healthcare AI, has recently demonstrated the significant potential impact of Artificial Intelligence (AI) on stroke care. In collaboration with Baptist Christian Hospital (BCH) in Tezpur, Assam, India, Qure.ai conducted a study focusing on the role of AI in improving stroke diagnosis and treatment times, especially in remote or resource-challenged settings.

The study, titled "Artificial Intelligence-based Automated CT Brain Interpretation to Accelerate Treatment for Acute Stroke in India: An Interrupted Time Series Study," evaluated the effectiveness of Qure.ai's AI-powered stroke detection solution, qER.

Stroke is the second leading cause of death worldwide and a major cause of disability, emphasizing the need for timely intervention. In India, it ranks as the third leading cause of death and sixth in disability. The first 60 minutes post-stroke, known as the Golden Hour, are critical for intervention, as prompt medical treatment can significantly enhance recovery outcomes. The high economic burden of stroke-related hospitalization further underscores the importance of immediate medical attention.

BCH Tezpur is a 130-bedded charitable hospital under the Emmanuel Health Association. It has an ER with ten beds and provides both outpatient and inpatient services. BCH Tezpur does not have a neurologist in-house and depends on a tele-radiologist for the NCCT report analysis, which often takes hours. The nearest comprehensive stroke hospital is in Guwahati, 180 km away, making faster stroke diagnosis and intervention a challenge.

With only one neurologist per million people in India, often concentrated in urban areas, the Qure-BCH Tezpur study underscores the potential of AI-powered solutions to support clinicians in delivering superior patient care and transforming stroke management.

Qure.ai's solutions aim to enhance diagnostic accuracy and efficiency, ultimately improving patient outcomes through earlier detection. The qER solution analyzes head CT scans within minutes, highlighting critical findings and enabling physicians to quickly identify stroke patients and initiate treatment faster.

Key findings from the <a href="https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0003351">Qure-Tezpur study</a> include:

"Like BCH Tezpur, there are many hospitals across the world, particularly in LMICs, that are the first line of care for stroke patients. Given the challenges of accessibility to alternate superspecialty care centers, the treatment adequacy and timeliness in these centers decides the patient outcomes, and possibly post stroke quality of life for patients. It is heartwarming to see the real-world impact of our AI solution for stroke care at BCH, and we aim to see a similar transformation worldwide.” said Anumeha Srivastava, Chief Business Officer - Neurology of Qure.ai.

Dr. Jacob Johnson, Medical Director at Baptist Christian Hospital, remarked, "Integrating Qure.ai's AI-powered stroke detection solution has transformed our approach to stroke care. The ability to quickly and accurately diagnose strokes has allowed us to provide timely interventions, drastically improving patient outcomes in our hospital."

The findings from the Qure – BCH Tezpur collaboration indicate that AI solutions and technological advancements are helping to reshape the stroke care landscape. Qure.ai's stroke solution, qER, alongside the Qure App for streamlined care coordination, is enhancing access to neurocritical care in several Indian hospitals. Wider adoption of this AI-driven approach is the future of stroke care – it can facilitate faster interventions, potentially setting a new standard for treatment and significantly improve patient outcomes globally.

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AI Helps Doctors Treat Stroke Faster: Qure.ai Study Reveals Significant Real-World Impact

First of four NHS sites roll out head-CT AI to highlight critical head injury scans&nbsp;&nbsp;

A pioneering new multi-NHS site initiative has gone live, aiming to improve radiology report turnaround times for non-contrast CT head scans by creating prioritised reporting worklists of critical findings. This will allow Emergency Department (ED) clinicians at the Queen Elizabeth University Hospital in Glasgow to make faster decisions about the care, management and discharge of patients with head injuries.&nbsp;&nbsp;

The project called ACcEPT (Assess the Clinical Effectiveness in Prioritising CT Heads) commenced at NHS Greater Glasgow and Clyde, the first of four planned NHS sites across the UK, utilising qER, the head CT Artificial Intelligence (AI) solution from Qure.ai. The AI roll-out comes in time to assist with mid-winter frontline accidents &amp; emergency pressures.&nbsp;&nbsp;

In the first initial weeks of the head CT AI implementation over the 2023/24 winter period, qER analysed 651 non-contrast head CTs, detecting 128 head injuries including cranial fractures, intracranial haemorrhage (ICH), mass effect and mid-line shift within the brain. The intracranial pathologies were identified and prioritised by the qER AI solution as critical findings for radiologist review, confirmation, treatment planning and / or discharge out of ED.&nbsp;&nbsp;

“Emergency Departments across the country continue to face challenges over winter with one person presenting at a UK ED every 90 seconds, potentially requiring brain imaging. By utilising the opportunities of innovative AI to help prioritise urgent cases, we will look to deliver critical interventions whilst improving workflow and time in the ED for patients with normal scans. The study looks to provide evidence to support adoption of AI across 4 centres in the UK. We hope this will support clinical teams in decision making to deliver critical clinical care, reassurance and, when appropriate, discharge, releasing capacity and space for patients in our pressured system,” states Professor David Lowe, Professor of Health Innovation at the University of Glasgow and Emergency Medicine Consultant at NHS Greater Glasgow and Clyde.&nbsp;&nbsp;

Denise Brown, Director of Digital Services at NHS Greater Glasgow and Clyde states, “It is important to establish reliable evidence on the impact and value of AI solutions, and to determine how they best support clinical decision making. Our Digital Strategy’s Enabled by AI Programme brings together NHS Greater Glasgow &amp; Clyde’s expertise on research, innovation and the operation of AI solutions at scale, while working closely with colleagues in academia.”&nbsp;

Darren Stephens, Senior Vice President &amp; Commercial Head, UK and Europe at Qure.ai states, “This is an exciting step forward for AI in NHS Emergency Departments. Providing digital health tools that can create calm and give informed prioritisation of urgent cases to support stretched clinical teams, especially at night or weekends, is very advantageous. It may help reduce CT scan-to-reporting turnaround times and give rapid alerts of critical findings that will boost the speed of treatment given to patients.”&nbsp;&nbsp;

The ACcEPT qER study is award funded by the NHS AI Lab programme run by the NHS Accelerated Access Collaborative (AAC) in partnership with the National Institute for Health Research (NIHR). It aims to evaluate the use of AI to support clinicians analysing the CT scans of patients with head injuries, leading to faster treatments and better outcomes for patients. It will assess the value of the AI tools in situations where there is a shortage of trained radiologists to analyse the scan images, particularly during out-of-hours.&nbsp;&nbsp;

The full ACcEPT collaboration team includes: medical imaging AI innovator, Qure.ai; Hardian Health for health economic evaluation; the University of Glasgow’s Digital Health Validation Lab (DHVL), a Living Laboratory for Precision Medicine project aimed at fast-tracking digital health technologies into clinical settings; West of Scotland Innovation Hub; NHS SafeHaven; NHS Greater Glasgow and Clyde; Oxford University Hospitals NHS Foundation Trust; Northumbria Healthcare NHS Foundation Trust; and Guy’s and St Thomas’ NHS Foundation Trust.&nbsp;&nbsp;

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Urgent findings from head-CT scans prioritised by AI at    NHS Greater Glasgow and Clyde to support winter A&E pressures 

Mumbai/Kozhikode, 19 March 2024: Qure.ai, a leading artificial intelligence solution provider for medical imaging, has announced its newest deployment in Aster MIMS Hospital, Kozhikode, to enhance stroke care and diagnosis. This collaboration introduces an innovative AI-powered Hub (Aster MIMS) &amp; Spoke (periphery hospitals) model for timely diagnosis and better care coordination for stroke-suspected patients across its spoke sites.&nbsp;&nbsp;

The key innovation at the heart of this hub and spoke model is Qure.ai's qER suite of solutions, an AI-enabled head CT solution deployed in conjunction with the Qure App care platform. Qure’s qER is capable of processing CT scans in less than three minutes, and the Qure app plays a crucial role in relaying real-time patient information and radiology images to multi-disciplinary teams at the hub site (Aster MIMS). This is especially crucial during suspected stroke cases, expediting life-saving interventions.&nbsp;

The Hub &amp; Spoke model envisions resource-challenged spoke hospitals connected to a central hub hospital, optimizing healthcare infrastructure utilization and facilitating seamless care coordination. As part of this collaboration, Aster MIMS Calicut, the hub hospital, will be connected with 4 spoke hospitals located on the peripheries of Kozhikode. Aster MIMS anticipates treating an annual influx of approximately 1500 stroke patients across the network, including 600 patients from the connected spoke sites.&nbsp;

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Dr. Ashraj V V, Sr. consultant and Director at Aster Institute of Neurosciences, said, “Stroke is a major health concern for every individual irrespective of their age. The AI-powered Hub &amp; Spoke model is a promising technology that ensures timely treatment for stroke patients. Qure.ai's care coordination app facilitates effective collaboration between healthcare professionals across the Hub &amp; Spoke network and helps in optimizing healthcare infrastructure.”&nbsp;

Dr. Abdurehiman KP, Sr. Consultant and Head of Neurology at Aster MIMS Calicut, said, “I’m very happy to be part of this newest deployment in Aster MIMS Hospital, Kozhikode, that advances stroke care and diagnosis. AI has upgraded many aspects of our lives, and healthcare is one of them. Qure.ai's AI-enabled head CT solution helps in faster stroke diagnosis and their care coordination app significantly reduces the Turnaround Time (TAT) for interventions through real-time case notifications and alerts across the Hub &amp; Spoke network.”&nbsp;

This initiative promises to revolutionize stroke care in resource-constrained settings by leveraging advanced medical imaging technology, enhancing the speed and accuracy of diagnosis, and facilitating effective collaboration between healthcare professionals across the Hub &amp; Spoke network.&nbsp;

Highlighting the significance of the partnership, Prashant Warier, CEO &amp; Co-Founder of Qure.ai, said, “Deploying our solutions at a super-speciality hospital like Aster MIMS, Kozhikode, is a stepping stone to making advanced healthcare accessible for some of India’s most remote locations. This model of deployment is a testament to AI’s potential for bridging the healthcare gap in India. This is a significant step towards battling the stroke care burden in India and a step closer to our vision of making healthcare accessible and affordable to everyone.”&nbsp;

qER, an advanced deep-learning software, screens head CT scans to identify intracranial haemorrhages and infarcts for prioritized clinical review, providing anatomical location identification and quantification, and ASPECTS scoring for stroke severity. qER also facilitates the identification of Large Vessel Occlusion on CT Angiography, aiding patient selection for Mechanical Thrombectomy, which would otherwise be delayed or missed. 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.

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Aster MIMS Kozhikode goes live with Qure.ai’s AI-enabled stroke care solution

Mumbai, 4th March 2024: Qure.ai, a leading AI-driven medical imaging solutions provider, announced its latest hub &amp; spoke network deployment at CMC Hospital, Ludhiana in partnership with Medtronic (India Medtronic Pvt. Ltd., a wholly-owned subsidiary of Medtronic plc). This initiative aims to elevate stroke care and diagnosis in Punjab. The innovative Hub-and-Spoke model, where CMC Ludhiana serves as the central hub and periphery hospitals as spokes is one of the many crucial deployments across the country.&nbsp;&nbsp;

As part of the collaboration, CMC Ludhiana will establish a network of spoke hospitals across Punjab to create an efficient network of periphery hospitals, connected to the central hub, giving every connected spoke site, equal access to the state-of-the-art neurocritical care team function at CMC Ludhiana. CMC Ludhiana is the first Advanced stroke center certified by the World Stroke Organization. Moreover, it is also a Collaborating Center of Excellence for stroke research under the Indian Council of Medical Research.&nbsp;

Stroke is a medical emergency that occurs when there is a sudden interruption of blood flow to a part of the brain. This interruption can be caused by either a blockage in the blood vessels (ischemic stroke) or the rupture of blood vessels (haemorrhagic stroke). Time to treatment is a critical element in determining the patient outcome in case of stroke. The "golden window" in stroke treatment is often between 4 to 6 hours after the onset of stroke symptoms. This is a critical window during which medical interventions like thrombolysis and mechanical thrombectomy are most effective.&nbsp;

At the heart of the collaboration lies Qure.ai’s AI-enabled head CT solution – qER. The deep learning-based software has the ability to process the CT scan and provide comprehensive findings within 3 minutes. The network of hub &amp; spoke is established on the care coordination platform – Qure App, facilitating seamless coordination between hub &amp; spokes. When a suspected stroke patient is admitted to a spoke hospital, qER swiftly processes their CT scan using AI. In the event of critical findings, a real-time alert is promptly sent to the hub site's specialized stroke team along with annotated findings on the CT scan, facilitating seamless communication between the hub and spoke teams via the Qure App. In case of advanced interventions like thrombectomy, the spoke team is promptly guided to transfer the patient to the hub site. The benefits are clear: faster triaging, access to real-time information, and seamless hub &amp; spokes coordination. &nbsp;

Dr. Jeyaraj Pandian, President-Elect, World Stroke Organization, and Principal (Dean) and Professor of Neurology, Christian Medical College, Ludhiana said, “Stroke is preventable and treatable, and the key lies in timely intervention. Our collaboration with <a href="http://www.qure.ai/" target="_blank">Qure.ai</a> and Medtronic signifies a major leap forward in redefining stroke care by harnessing the power of artificial intelligence. The hub and spoke model that we have adopted will transform how we approach stroke management, enabling swift, efficient, and life-saving interventions.”&nbsp;

The capability and availability of hospitals, especially those with specialized stroke units are fragmented across most parts of India. Often, the periphery hospitals lack neurocritical resources that can aid in faster diagnosis and treatment of stroke cases. This can be detrimental to the patient's prognosis and their quality of life.&nbsp;

Christian Medical College (CMC), Ludhiana, anticipates an annual footfall of hundreds of stroke patients at its spoke sites, reinforcing its commitment to delivering accessible and comprehensive healthcare services. Furthermore, they have also conducted a thorough analysis of patient demographics that revealed an average age of 59 ± 15 years and a predominantly middle-class socioeconomic background. This data underscores CMC's dedication to tailoring healthcare solutions to the specific needs of its community. Additionally, the network's potential coverage area extends to the Ludhiana district, reflecting its strategic approach to ensuring healthcare accessibility across a wide geographic region.&nbsp;

Michael Blackwell, VP &amp; MD, Medtronic India said, “Time is brain when stroke affects a patient. Having access to a stroke-ready center, speedy diagnosis and treatment can save many lives. At Medtronic, our aim is to support an ecosystem where healthcare has no limits and technology can be leveraged to address rapidly evolving patient needs. Our collaboration with Qure to advance stroke care in many locations across India is a step in that direction.”&nbsp;

Emphasizing the partnership's importance, Prashant Warier, CEO &amp; Co-Founder, Qure.ai, stated, "The deployment of our solution in collaboration with Medtronic at a specialized institution like CMC Ludhiana signifies a pivotal step in expanding cutting-edge healthcare services to the furthest corners of India. This unique deployment approach underscores the profound impact of artificial intelligence in narrowing the healthcare gaps within the nation. It stands as a remarkable leap towards easing the challenges of stroke care in our country and propels us closer to our overarching goal of making healthcare accessible and cost-effective for everyone." &nbsp;

qER, an advanced deep-learning software, utilizes cutting-edge technology to analyse head CT scans, pinpointing intracranial haemorrhages and infarcts for prioritized clinical assessment. The software offers crucial features such as anatomical location identification, precise quantification of ICH and infarct volumes, and ASPECTS scoring to assess stroke severity. Additionally, qER efficiently identifies Large Vessel Obstruction on CT Angiography, aiding in the selection of patients for Mechanical Thrombectomy, a crucial intervention that might otherwise be delayed or overlooked. The software includes a priority flag for critical cases, an overlay highlighting abnormal findings, and comprehensive reports that quantify detected abnormalities. qER is FDA, CE MDR cleared, with approval from multiple national regulators. The Qure App facilitates critical care coordination with timely alerts. &nbsp;

FDA certification link: <a href="https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K200921" target="_blank">https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K200921</a> &nbsp;

Patient demographics study in Ludhiana :&nbsp;

<a href="https://journals.sagepub.com/doi/full/10.1177/2396987317724052" target="_blank">https://journals.sagepub.com/doi/full/10.1177/2396987317724052</a>&nbsp;

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AI helps transform Stroke Care at CMC Ludhiana

Blackford and Qure.ai partner to deliver AI powered neurocritical solution for brain CT analysis to highlight critical findings that require immediate clinical attention.

<a href="https://www.blackfordanalysis.com/" target="_blank">Blackford</a>, the pioneering strategic AI platform and solutions provider, has partnered with Qure.ai, a leading provider of artificial intelligence (AI) solutions for radiology, to deploy the&nbsp;<a href="https://qure.ai/product/qer/" target="_blank">neurocritical AI solution, qER</a>, at&nbsp;<a href="https://www.mkuh.nhs.uk/" target="_blank">Milton Keynes University Hospital NHS Foundation Trust (MKUH).</a>

“Blackford is committed to delivering AI solutions that broaden clinical and operational AI usage and drive additional value for healthcare organisations and their patients,” said Blackford CEO Ben Panter. “Our model of partnering with best-of-breed AI providers like Qure.ai to tailor solutions via our tried-and-tested platform makes it easier and more efficient for healthcare providers like MKUH to evaluate and deploy AI and generate immediate and ongoing value.”

MKUH will use Qure’s qER for automating the detection of critical and life-threatening abnormalities in head CT scans, including intracranial haemorrhages (ICH) caused by trauma, accidents or strokes. It is an FDA cleared and EU MDR Class IIb certified solution, and will be used for all non-contrast CT scans at the Trust. The solution aids in triaging critical cases, within three minutes, in the emergency department, especially during out-of-hour shifts when a larger team may not be available.

“This is a great step forward for frontline A&amp;E patient care and we are delighted to partner with Blackford to bring qER to Milton Keynes University Hospital," said Darren Stephens, Senior Vice President &amp; Commercial Head UK and Europe of Qure.ai. “Our AI solution will help improve patient outcomes by providing timely and accurate detection of critical abnormalities, enabling clinicians to make informed decisions and take appropriate actions."

The partnership between Blackford and Qure.ai is part of an ongoing effort to leverage AI technology to enhance clinical decision-making. MKUH procured the Blackford Platform to underpin its AI strategy and make evaluation, adoption, monitoring, and support of AI more efficient.&nbsp;qER by Qure.ai&nbsp;is one of the first AI solutions to be successfully evaluated and deployed via the Blackford Platform at MKUH. By automating the detection of critical abnormalities in head CT scans, qER can help clinicians save time and focus on providing the best possible care for patients.

“Our collaboration with Blackford and&nbsp;<a href="https://www.globenewswire.com/Tracker?data=wineedzsJUGYcXHtfW6SJRJpOJRV6lVAMl9HJVrNGYTQwi3dqlr7khzScW5_3Cc4" target="_blank">Qure.ai</a>&nbsp;empowers our Emergency Department with AI to swiftly identify critical head CTs scans, enabling us to prioritise and provide timely care to those who require it most. By harnessing the power of AI, we can improve clinical workflow efficiency therefore ensuring that we deliver the safest and most effective care for all of our patients.” said Andrew Scott, PACS Manager / Imaging IT Systems Lead Imaging Department of Milton Keynes University Hospital NHS Foundation Trust.

Channel Partners:&nbsp;Intelerad, Blackford

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Neurocritical AI solution to be deployed into A&E at Milton Keynes University Hospital NHS Foundation Trust

Qure.ai, a global leader in AI-based radiology solutions, has been announced as one of the prestigious awardees of the Japan Smart Healthy Aging Initiative QuickFire Challenge, organized by Johnson &amp; Johnson Innovation LLC in Japan.

Qure.ai’s idea for the QuickFire Challenge focuses on revolutionizing&nbsp;stroke diagnosis and treatment. Their AI-based head CT interpretation software,&nbsp;qER, not only detects abnormalities in non-contrast head CT scans but also has an additional capability to identify Large Vessel Occlusion (LVO) on NCCT. The advanced technology aims to triage and flag ischemic stroke patients by detecting core and LVO signs on non-contrast Head CT and reduce the treatment times.

Globally, the burden of stroke has increased significantly, and in Japan, with an aging population of nearly 30 percent, stroke is among the top 5 causes of mortality*. Large Vessel Occlusion (LVO) ischaemic stroke poses significant challenges due to time-sensitive management. By optimizing the workflow and expediting diagnosis, qER seeks to improve stroke outcomes, reduce morbidity, and save lives among the aging population.

As one of the awardees of the Japan Smart Healthy Aging QuickFire Challenge, Qure.ai will be granted access to the Johnson &amp; Johnson – Innovation JLABS @ Shanghai, and mentorship from experts across the Johnson &amp; Johnson Family of Companies and also will share the $300,000 grant money alongside the other awardees.

Commenting on the award,&nbsp;Prashant Warier, CEO and Co-founder of Qure.ai, said, “We are honoured to be selected as an awardee and are dedicated to contributing to transforming healthcare in Japan. This mentorship will provide market insights, project opportunities, and network support, enabling us to expand our reach and impact “.

Other winners of the challenge are BrilliantStrings Therapeutics (USA), Kinexcs (Singapore), and, Octotix (USA).

For more information about the SHAI QFC, please visit –&nbsp;<a href="https://www.jnj.co.jp/smart-healthy-aging_eng">https://www.jnj.co.jp/smart-healthy-aging_eng</a>

QuickFire Challenge:&nbsp;<a href="https://jnjinnovation.com/innovation-challenges/japan-smart-healthy-aging-quickfire-challenge">https://jnjinnovation.com/innovation-challenges/japan-smart-healthy-aging-quickfire-challenge</a>

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Qure.ai Wins Japan Smart Healthy Aging Initiative QuickFire Challenge Organized by Johnson & Johnson Innovation

<a target="_blank" href="https://www.medtronic.com/in-en/index.html">Medtronic India</a>&nbsp;has announced a groundbreaking partnership with AI innovator Qure.ai, aiming to revolutionize stroke management. This collaboration seeks to integrate Qure's AI-powered solutions into comprehensive and primary stroke centers, connecting them via a 'hub-and-spoke' network. The goal is to expedite stroke patients' identification, decision-making, and triaging, thereby enhancing patient outcomes.

A stroke is a medical emergency that arises from a blood flow blockage to the brain. Timely treatment is often hindered due to a lack of symptom awareness, inadequate patient pathways, and the absence of specific physician training for correctly interpreting CT scans. These challenges can result in increased stroke-related morbidity and mortality.

Qure.ai has developed an impressive suite of AI solutions to streamline stroke care. Their&nbsp;<a target="_blank" href="https://www.qure.ai/product/qer/?_gl=1*11hfxsu*_up*MQ..*_ga*MTkyNzE3NDQ3Ni4xNjgwNTk5ODY1*_ga_7Y7T97E9GY*MTY4MDU5OTg2NC4xLjAuMTY4MDU5OTg2NC4wLjAuMA..">qER&nbsp;</a>system quickly interprets head CT scans and other crucial parameters, reducing the usual reading and diagnosis time from approximately 65 minutes to an astounding 2 minutes. This information is synchronized with the&nbsp;<a target="_blank" href="https://app.qure.ai/landing-page">Qure app</a>, which fosters efficient communication among multidisciplinary teams across different hospitals.

<a target="_blank" href="https://www.linkedin.com/in/michael-blackwell-96aa632/">Michael Blackwell</a>, Vice President &amp; Managing Director of Medtronic India, expressed enthusiasm about the partnership. He remarked that integrating AI with healthcare technology will allow for rapid, personalized diagnosis and treatment, potentially saving lives. The collaboration with Qure.ai further underscores Medtronic's commitment to improving stroke care.

<a target="_blank" href="https://www.linkedin.com/in/pwarier/">Prashant Warier</a>, CEO &amp; Co-Founder of Qure.ai, echoed this sentiment, stating that their collaboration will enhance the diagnostic accuracy and speed of healthcare providers and improve hospital operational efficiency. This partnership aligns with Qure.ai's mission to leverage AI to improve patient care and promote equitable healthcare.

In India, around 1.8 million patients suffer a stroke annually. Swift treatment within the first 4.5 hours, or in severe cases, within 24 hours from symptom onset, can drastically improve outcomes. Using&nbsp;AI tools&nbsp;to support the entire stroke care process can minimize delays and gaps in care, ensuring that stroke patients receive timely and efficient treatment, particularly in a hub-and-spoke network.

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Medtronic and Qure.ai partner to advance stroke management using artificial intelligence (AI) in India

qER-Quant will help enable faster diagnosis and help track patient progression over time

New York, 17th Aug 2021:&nbsp;Leading medical image AI provider Qure.ai has announced US FDA 510(k) clearance for its brain CT quantification product qER-Quant. Clinicians in the US can now use this tool to rapidly and precisely assess the severity of injury in patients with conditions like traumatic brain injury, hemorrhagic stroke, and hydrocephalus and to track the progression of pathology over time.

CT scans are the most widely used exam for brain injuries and are used to help diagnose millions of patients that visit the emergency room every year. AI assistance speeds up treatment and transfer decisions, helps monitor patients more closely and reduces the chances of diagnostic errors.

Ajith Thomas MD, Associate Professor of Neurosurgery, Harvard Medical School and Co-Director, Brain Aneurysm Institute, Beth Israel Deaconess Medical Center said, “The use of AI will be transformative in the management of traumatic brain injury by obtaining an expedient and accurate diagnosis. Congratulations to Qure.ai for being at the forefront of this paradigm shift!”

“Qure.ai’s technology makes it possible to systematically measure brain hemorrhages precisely and rapidly in patients with stroke or trauma. Fully automated quantification could soon become the standard of care.” says Dr Johan Wasselius, Interventional Neuroradiologist at the Skåne University Hospital and Lund University, Sweden.

“This FDA clearance adds quantification, outlining and measurement capabilities to Qure.ai’s first clearance for triage and notification of critical brain markers. We are excited about bringing a complete suite of capabilities to clinicians who deal with critical head CT scans.” said Dr. Pooja Rao, Co-Founder and R&amp;D head, Qure.ai.

“We’ve always built products to solve real customer challenges and qER Quant is another example of the same. We worked on this capability based on customer feedback from radiologists, neurologists, and ER physicians who expressed the need to get automated volume measurements on neuro scans to assess patient progress as well as safe discharge decisions. It helps us offer a more comprehensive suite of AI tools to our US clinical partners.” said Prashant Warier, CEO and co-founder, Qure.ai.

The FDA clearance and a summary of the performance of the software is available at this link. The AI tool is also cleared for marketing in the EU, and is currently used by teleradiology providers, emergency care physicians and radiologists at more than 40 clinical sites, helping process thousands of scans every day.

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Qure.ai bags second FDA clearance for Brain CT scan AI

Qure.ai, a leading developer of artificial intelligence (AI) software in the healthcare space, has recently achieved a significant regulatory milestone by securing 510(k) clearance from the U.S. Food and Drug Administration (FDA) for its innovative qER-Quant head CT quantification software. This clearance further solidifies Qure.ai’s standing as a global leader in AI-driven medical solutions, particularly in the domain of critical care imaging.

The qER-Quant software is specifically designed to assist in the assessment and quantification of injury severity in patients suffering from serious neurological conditions. These conditions include traumatic brain injury (TBI), hemorrhagic stroke, and hydrocephalus, which are often complex and time-sensitive cases requiring immediate and precise medical attention. 

The software uses advanced AI algorithms to provide rapid analysis of head CT scans, enabling medical professionals to more accurately measure the extent of brain injuries and other pathologies. This facilitates informed clinical decision-making, ensuring that patients receive timely and appropriate treatment.

In addition to its core functionality for initial injury assessment, qER-Quant is also equipped with tools to monitor the progression of these conditions over time. By offering clinicians the ability to track changes in brain pathology, the software becomes a valuable resource not just in emergency settings but also in long-term care and recovery management. This capability is especially critical in cases of progressive diseases or conditions that require ongoing observation, where subtle changes in the patient’s condition could have significant implications for treatment plans.

Qure.ai has emphasized that qER-Quant is a significant advancement in the field of medical imaging, as it introduces an unprecedented level of precision and automation in head CT scan interpretation. This innovation reduces the margin for human error, accelerates diagnosis, and enhances the overall standard of care for patients with complex brain injuries and disorders. The software’s approval by the FDA underscores the growing importance of AI in modern healthcare, and Qure.ai’s ongoing commitment to developing cutting-edge tools that improve patient outcomes. As healthcare systems worldwide continue to adopt AI technologies, qER-Quant is positioned to make a lasting impact, streamlining the management of critical neurological conditions and transforming the way radiologists and clinicians approach brain injury assessment.

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Qure.ai secures FDA clearance for qER-Quant

The UK National Health Service (NHS) is currently piloting a groundbreaking artificial intelligence (AI) system that has the potential to revolutionize the way severe injuries are identified and treated in emergency settings. This cutting-edge technology, designed to quickly analyze CT scans, aims to expedite the diagnosis process and enable rapid treatment for patients with critical conditions.

The program, which is being developed by Qure.ai, a leading healthcare technology company, is currently undergoing rigorous testing at three prominent NHS trusts: Guys' and St Thomas', King's College Hospital Foundation, and the Northumbria Foundation. These pilot sites were carefully selected to assess the effectiveness and feasibility of implementing the AI system in real-world clinical settings.

At the heart of this innovative technology is a sophisticated algorithm that can rapidly analyze CT scans and identify severe injuries with remarkable accuracy. By leveraging advanced machine learning techniques and deep neural networks, the system can quickly flag cases that require immediate attention, alerting radiologists to prioritize their review and take swift action.

Pooja Rao, the co-founder of Qure.ai, emphasized the potential impact of this technology on patient outcomes. In cases of brain bleeding, for example, where every minute counts, the AI system could accelerate diagnosis by up to an hour during busy times. This significant reduction in the time taken to identify critical injuries can make a life-saving difference, enabling healthcare professionals to initiate appropriate treatment promptly.

The benefits of this AI-powered system extend beyond improving patient outcomes. By automating the initial analysis of CT scans, the technology can help alleviate the workload on radiologists, who often face a high volume of cases to review. This not only allows them to focus their expertise on the most critical cases but also reduces the risk of human error and ensures a more consistent and reliable diagnostic process.

The NHS recognizes the immense potential of this AI system and has ambitious plans for its future implementation. Following the successful completion of the pilot program, the NHS aims to extend the trial to an additional six to eight hospital trusts over the next two years. This expansion will provide valuable insights into the scalability and adaptability of the technology across different healthcare settings.

If the trials prove successful and the AI system demonstrates its effectiveness in improving patient outcomes and streamlining diagnostic processes, the NHS envisions a broader implementation across its network of hospitals. This would mark a significant milestone in the integration of AI in healthcare, setting a new standard for the early detection and treatment of severe injuries.

However, the implementation of such advanced technology also brings challenges that need to be addressed. Ensuring the accuracy and reliability of the AI system is of utmost importance, as any errors or false positives could have serious consequences for patient care. Rigorous validation and continuous monitoring will be essential to maintain the highest standards of performance and safety.

Furthermore, the integration of AI in healthcare requires a collaborative effort between technology developers, healthcare professionals, and policymakers. Training and education programs will be necessary to ensure that radiologists and other healthcare staff are equipped with the knowledge and skills to effectively utilize the AI system and interpret its results.

The NHS's pilot program of Qure.ai's AI system for identifying severe injuries in CT scans represents a significant step forward in the application of artificial intelligence in healthcare. By harnessing the power of advanced algorithms and machine learning, this technology has the potential to transform the way critical conditions are diagnosed and treated, ultimately saving lives and improving patient outcomes. As the NHS continues to explore and expand the use of AI in healthcare, it is clear that this innovative approach holds immense promise for the future of medical care in the UK and beyond.

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NHS is piloting AI-assisted CT head scans that can quickly spot patients with serious injuries

Seeking to address the urgent need for faster stroke and concussion diagnoses, <a href="https://www.businessinsider.in/tech/news/a-small-hospital-assam-is-using-ai-to-detect-strokes-in-tea-planters/articleshow/84194042.cms">Assam's Baptist Christian Hospital</a>, in the Tezpur town foothills of the Himalayas, has adopted Qure.ai's artificial intelligence solution for rapid brain CT scan analysis.

The hospital predominantly serves tea plantation workers, a population heavily impacted by stroke—one of the significant causes of death in the region.

Qure.ai's AI-enabled solution, the qER, drastically reduces diagnosis time, providing potentially life-saving benefits. 

Rapid intervention is crucial, with strokes leading to millions of brain cell deaths per minute. 

Qure.ai co-founder Prashant Warrier said the qER could significantly speed up this process.

Dr. Jemin J Webster of Baptist Christian Hospital has praised the technology's efficiency, stating that the hospital has been diagnosing around 100 patients monthly since it implemented the technology in early 2021. 

Qure.ai anonymizes all data transferred to ensure users' privacy and continuously publishes its accuracy rate, regularly updating its technology.

Recognized globally for its ground-breaking AI solutions, Qure.ai has not only received certifications from the US FDA and Europe's CE but has also been validated by the World Health Organization for its tuberculosis diagnostic software.

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A small hospital in a remote corner of Assam is using AI to detect strokes in tea planters

Today, the UK Department of Health and Social Care announced that Qure.ai has been selected as one of the winners of the Artificial Intelligence in Health and Care Award, sponsored by the UK government. 

Qure.ai is a 5-year-old Sequoia-funded company builds Artificial Intelligence (AI) powered solutions to facilitate identification and treatment of stroke and head injuries. The Award has been instituted by the Accelerated Access Collaborative (AAC) in partnership with NHSX and the National Institute for Health Research (NIHR). T

he consortium is making £140 million available over four years in funding and support for promising AI technologies.

The award will drive Qure.ai’s mission to gather real-world evidence for its qER tool in an ER setting, in partnership with the NHS Guy’s and St. Thomas’ Foundation Trust, NHS King’s College Hospital Foundation Trust, NHS Northumbria Healthcare Foundation Trust and other key Major Trauma focused NHS trusts across the country.

qER is Qure.ai’s AI platform that identifies a range of critical markers on head CT scans, such as bleeds, strokes and fractures.

 The technology is CE-marked and received United States FDA clearance in 2020. qER will now be deployed in Accident and Emergency (A&amp;E) departments in the UK to improve diagnostic turn-around times for these critical conditions and help reduce missed diagnoses.

The NHS has seen a significant rise in A&amp;E footfalls as well as growing volumes and complexity of imaging, with CT and MRI volumes increasing by an average of 10% (over half a million scans) per year, while patient wait times in the A&amp;E have been steadily increasing too.

 For better patient outcomes, the time to diagnosis and treatment is critical, particularly for patients with neuro presentations such as head trauma or stroke.

Dr. Haris Shuaib, Consultant Physicist, Head of Clinical Scientific Computing at Guy’s and St Thomas’ NHS Foundation Trust said, “Our out-of-hours radiology reporting service would benefit greatly from an effective triaging and prioritisation system. With the qER system from Qure we hope to be able to manage critical findings like intracranial hemorrhage even more effectively.”

Dr Hugh Harvey, Managing Director, Hardian Health- “Winning a Phase 3 AAC award is a testimony to the strong consortium that has come together to support deployment and scaling of Qure’s market-leading qER software. 

Hardian Health is truly excited to be part of this fantastic consortium. We will be conducting cost-effectiveness analysis of the care pathways by involving all stakeholders, from NHS clinicians to patient advocacy groups”.

“We are excited about this Award from NHSX”, says Dr. Pooja Rao, R&amp;D Head and co-founder of Qure.ai. 

“This NHSX grant will help us demonstrate that appropriate use of AI technology leads to better patient outcomes and accrues economic benefits to the NHS system. It paves the way for wider adoption of Qure’s technology in the UK”.

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Qure.ai’s Brain CT AI wins funding from the NHS

The role of artificial intelligence (AI) in radiology is ever-expanding, with new startups focusing on improving imaging diagnosis, particularly in stroke triage, as the incidence of stroke and neurovascular disease continues to surge globally. 

Pooja Rao, Ph.D., co-founder and head of research and development at <a href="http://qure.ai">Qure.ai</a>, states that while the industry is yet to rely on AI tools for diagnosis entirely, its use is accelerating in research and development, particularly in specialties like interventional radiology and neurosurgery.

Qure.ai's <a href="https://www.radiologytoday.net/archive/rtSO20p14.shtml">FDA 510(k) cleared tool</a>, qER, decreases the time to action by up to 97% by detecting critical markers in head CT scans and immediately alerting clinicians.

Rao states that every bit of help AI tools can offer in this complex process directly improves patient outcomes and decreases the risk of death or permanent disability.

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