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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

CREATE is a
multi-country, prospective study led by
AstraZeneca and Qure.ai to assess the
impact of AI for triaging incidental
pulmonary nodules (IPN) detected on
routine chest X-rays and to expedite
appropriate downstream care for
suspicious nodules. Conducted across
23 centers in Egypt, India, Indonesia,
Mexico, and Turkey, CREATE is among
the largest real-world studies focused
on AI-enabled triage and loop closure
from CXR to lung cancer diagnosis.

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Study Reveals AI’s Ability to Detect Lung Cancer Risk in Younger, Non-Smoking Individuals

Lung cancer is the leading cause of cancer-related death worldwide, with diagnosis often occurring at late stages when treatment options are limited. This issue is particularly acute in resource-limited settings, where healthcare infrastructure is often underdeveloped,&nbsp;workforces are stretched, and economic constraints prevail.&nbsp;

A bold partnership between Qure.ai and AstraZeneca, as a commitment to the World Economic Forum’s EDISON Alliance 1 Billion Lives Challenge, set out to <a href="https://www.qure.ai/product/lung-nodule-management" target="_blank">apply AI to routine chest X-rays</a>, illustrating the role AI can play in providing a low-cost, scalable pathway to help identify lung cancer risk earlier.&nbsp;

<a href="https://www.qure.ai/news_press_coverages/A-new-era-for-lung-cancer-detection-AI-enabled-risk-assessment-reaches-5-million-people-around-the-world" target="_blank">Achieving the milestone of five million scans</a> across more than 20 countries, marks an important step forward. It provides real-world evidence for AI’s role in changing the lung cancer narrative that clinicians, healthcare providers, and country-level policy shapers can draw upon to enact positive change.&nbsp;&nbsp;

To gain your copy of an executive summary impact report, and dive into the data and real-life stories redefining early cancer care, register here:&nbsp;

Download Report - 'The Power of AI to evaluate lung cancer risk'

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Unlocking the Power of AI for Early Lung Cancer Detection

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

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

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

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

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

Fill the form for full report

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AI Adoption for X-rays : A roadmap for future

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

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

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

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

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

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

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

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

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

For full case study

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

In a recent pilot study at Frimley Health NHS Foundation Trust, Qure.ai’s AI-driven radiology tool, qXR, has demonstrated significant potential to ease the workload of consultant radiologists. The study aimed to assess qXR's ability to categorize chest X-rays (CXRs) as normal or abnormal, targeting a portion of the caseload—mainly GP and outpatient requests—which typically consists of 40% normal CXRs. By automating this triage process, the AI tool could redirect normal cases to radiographers, freeing up consultants to focus on complex imaging work.

The early results are promising: qXR showed a remarkable 99.7% accuracy in identifying normal CXRs. This efficiency translates to a potential reduction of up to 58% in radiologists' caseloads, saving them as much as two hours per day. With this time, radiologists can dedicate more attention to intricate diagnostic work, enhancing the overall effectiveness and responsiveness of radiology services.

Beyond workload management, qXR’s impact on patient care is noteworthy. The AI tool successfully flagged all cancer cases, including subtle nodules that might otherwise be overlooked. This ability to identify high-risk, early-stage lung cancer cases is a breakthrough, supporting earlier diagnosis and treatment, which are crucial for improving survival rates.

Dr. Amrita Kumar, a Consultant Radiologist and AI Clinical Lead at Frimley Health, highlighted the transformative role of AI, noting how it enables radiologists to prioritize complex cases while streamlining routine workflows. Darren Stephens from Qure.ai echoed this sentiment, emphasizing AI’s role in addressing the ongoing radiologist shortage, projected to reach 40% by 2027 according to the Royal College of Radiologists. As demand for radiology services grows, this study illustrates the promising potential of AI like qXR in relieving pressure on human resources, ensuring efficient and high-quality patient care across the healthcare system. 

Frimley Health’s pilot of qXR marks a step forward in integrating AI into clinical settings, showcasing how innovative technology can address resource constraints while advancing patient outcomes.

Please fill out the form to access full case study and learn how to leverage AI for medical imaging efficiency gains.

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AI Chest X-ray triage of normal / abnormal boosts radiology efficiency in NHS

LungIMPACT trial starts gathering real-world evidence with aim of saving lives now and into the future.

A collaborative study between UK academia, NHS hospitals and AI innovator Qure.ai has commenced to gather real-world evidence of AI-assisted diagnosis of lung cancer, which could help save thousands of lives.&nbsp;

The ‘LungIMPACT’ trial is using Qure’s qXR (CE Class IIb per EU MDR certified) solution to triage chest X-rays referred by GPs with the aim of identifying the presence of suspected lung abnormalities and give immediate reporting. This may then enable a patient to be referred for a same-day CT scan if lung cancer is suspected, speeding up access to a confirmed diagnosis and treatment planning.&nbsp;&nbsp;

The trial is now underway with Qure’s AI tool implemented at two NHS hospital Trusts, further NHS sites will also be deployed and ready to contribute to the study in a couple of months.&nbsp;

“Every year in the UK more than 35,500 people lose their lives due to lung cancer. We know that the speed of diagnosis is critical to achieve the best outcomes in lung cancer and to reduce stress and worry for patients. We have previously found that only a 15-day reduction in time to diagnosis increases survival by 200 days and immediate action on a chest X-ray that is suspicious for lung cancer reduces time to diagnosis by 30 days. AI may be a way to identify suspicious chest X-rays rapidly. Studies with AI are needed to evaluate the clinical value and impact to ensure safe and effective implementation,” states Professor David Baldwin, Chair of the UK Clinical Expert Group for Lung Cancer and Mesothelioma; National Clinical Lead for Lung Cancer, NHSE/I; Clinical Advisor to the UK National Screening Committee, Department of Health and Social Care; Respiratory Consultant at Nottingham University Hospitals NHS Trust; and Honorary Professor of Medicine at the University of Nottingham.&nbsp;&nbsp;

“We are delighted that the first hospital sites involved in the LungIMPACT trial are now live and the collaboration is gathering pace. The earlier cancer can be detected, the better chance patients have of survival. AI can be helpful in expediting diagnosis, and we hope that studies like this will gather the evidence needed to validate its role,” states Darren Stephens, Senior Vice President &amp; Commercial Head UK and Europe of Qure.ai.&nbsp;

The work was commissioned and funded by the NHS Cancer Programme, with the support of SBRI Healthcare and the NHS Accelerated Access Collaborative.&nbsp;&nbsp;

The NHS and academic teams have designed the study and all data will be analysed and reported independently from Qure.ai. Nottingham is leading the research on the back of the pioneering work on national rapid diagnostic pathways, AI imaging research and cancer screening.&nbsp;

It is led jointly by Professor David Baldwin, and Dr Nick Woznitza, a Consultant Radiographer at University College London Hospitals (UCLH) NHS Foundation Trust, and Clinical Academic at Canterbury Christ Church University. It also involves the expertise of Dr Richard Lee, National Institute for Health Research Specialty Lead Screening, Prevention and Early Detection, Dr Neal Navani, Senior Clinical Lead of the UK National Lung Cancer Audit.&nbsp;&nbsp;

Channel Partners:&nbsp;GE HealthCare, Magentus

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Accelerating lung cancer diagnosis through LungIMPACT trial

In the diverse landscape of India, a tale of two cities unfolds, separated by a mere 390 kilometers yet worlds apart in their realities. Mumbai, the bustling metropolis, stands tall with its glittering skyline, a symbol of India's economic might. In stark contrast, Chinchpada, nestled in the remote tribal lands of Maharashtra, paints a picture of development challenges and healthcare disparities. Yet, despite the chasm of their economic circumstances, both face a common enemy: the relentless onslaught of COVID-19 and the ancient scourge of Tuberculosis (TB).

Amidst this narrative of contrasts, a glimmer of hope emerges, powered by the transformative potential of Artificial Intelligence (AI). Enter Qure.ai, a trailblazer in AI-driven healthcare solutions, armed with its innovative chest X-ray screening tool, qXR. Born from the visionary SAMRIDH Grant, a collaborative endeavor between USAID and IPE Global, qXR holds the promise of swift TB detection, delivering results within mere minutes.

The brilliance of qXR lies not just in its technical prowess, but in its ability to bridge the divide between the disparate healthcare landscapes of Mumbai and Chinchpada. In the crowded clinics of Mumbai, where the pulse of the city thrums with urgency, qXR steps in as a silent guardian, swiftly identifying the telltale signs of TB amidst the chaos. Equally impressive is its impact in the sparse healthcare facilities of Chinchpada, where resources are scarce, and medical expertise is often stretched thin. Here, qXR becomes a beacon of hope, empowering clinicians to make accurate diagnoses and deliver timely care to those who need it most.

On the frontlines of this battle against TB, clinicians bear witness to the transformative power of qXR. Once overwhelmed by the sheer volume of patients and the complexity of diagnosis, they now speak of renewed hope and empowerment. With qXR by their side, they can swiftly identify those in need of immediate attention, ensuring that no one slips through the cracks. The impact of this technology extends beyond mere numbers; it is reflected in the smiles of those who have been given a second chance at life, and in the renewed determination of healthcare workers to fight the good fight.

As the story of Mumbai and Chinchpada transpires, Qure.ai's AI solution stands as a testament to the power of technology to bridge gaps and shatter barriers. It seamlessly integrates into the diverse healthcare settings of these two cities, adapting to their unique challenges and proving that innovation knows no boundaries. With each successful diagnosis, with each life saved, qXR reinforces the notion that AI is not just a tool, but a catalyst for change, a great equalizer in the face of health disparities.

This is a story of hope, of resilience, and of the indomitable human spirit. It is a tale of how technology can be harnessed to combat healthcare inequities, to bring light to the darkest corners, and to ensure that no one is left behind. As we bear witness to this transformative journey, we are reminded that the future of healthcare lies in the hands of those who dare to dream, those who seek to harness the power of innovation for the greater good.

So let us embark on this journey together, and bear witness to the unfolding of a new chapter in India's healthcare narrative. Let us celebrate the triumph of AI over adversity, and let us be inspired by the countless lives that have been touched by its transformative power. For in the end, this is not just a story of technology, but a testament to the resilience of the human spirit, and the unwavering commitment to building a healthier, more equitable world.

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A tale of two cities: AI for Health Equity

In the tapestry of Eastern India lies Bihar's Purnia District, a land where tales of human resilience are woven amidst the threads of overwhelming healthcare adversities. Here, in a region where incomes hover at a mere USD 5 per month, the specter of poverty looms large, casting its shadow over every aspect of life. Yet, amidst this landscape of chronic impoverishment, a glimmer of hope emerges, illuminating a path towards change and progress.

At the heart of this transformation is the Christian Medical Centre and Hospital (CMCH), an oasis of compassion and dedication in a desert of healthcare disparities. Led by the indomitable Dr. Alexander Philip, who has chosen to dedicate his medical expertise to the people of Purnia, CMCH stands as a bulwark against the onslaught of disease and despair.

But even as Dr. Philip and his team battle against the scourge of Tuberculosis (TB) and the shadow of COVID-19, they find an unlikely ally in the form of Artificial Intelligence (AI). Through a groundbreaking collaboration born of the SAMRIDH Grant, Qure.ai has deployed its cutting-edge AI solution, qXR, at CMCH Purnia. This powerful tool, designed to detect TB faster and more accurately than ever before, is a beacon of hope in a region where the doctor-patient ratio is staggeringly skewed.

The impact of qXR is already being felt, with over 2,500 X-rays processed seamlessly in the early stages of the initiative. From these scans, a staggering 299 TB-presumptive patients have been identified, a testament to the power of early detection and the potential for AI to transform healthcare at the grassroots level.

But the reach of this initiative extends far beyond the walls of CMCH. In school compounds and community hubs across Purnia, the qXR technology is being put to work, screening children and educating communities about the insidious threat of TB. Through engaging skits and songs performed in the local dialect, the essence of medical innovation is being woven into the fabric of Purnia's culture, demonstrating the transformative power of technology when it is paired with compassion and understanding.

As we journey deeper into Purnia's story, we see a tale of resilience and hope emerging from the shadows of adversity. The partnership between SAMRIDH and Qure.ai is more than just a technological breakthrough; it is a reminder that even in the face of the most daunting challenges, change is possible when we harness the power of innovation and collaboration.

Through the lens of Purnia, we see a microcosm of the global fight against TB, a disease that has long preyed upon the most vulnerable among us. But we also see a glimmer of what is possible when we combine the power of AI with the dedication of healthcare workers like Dr. Philip. In the heartlands of Bihar, a revolution is taking place, one that has the potential to reshape the landscape of TB detection and treatment not just in India, but around the world.

Let us embark upon this journey together, and bear witness to the incredible story unfolding in Purnia. Let us marvel at the power of AI to transform lives, and let us be inspired by the resilience and determination of those who have dedicated themselves to the fight against TB. In doing so, we will not only gain a deeper understanding of the challenges that lie ahead, but also a renewed sense of hope for a future where no one is left behind in the battle against disease.

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AI helps overcome healthcare challenges in Bihar

AI-based chest X-ray (CXR) screening for tuberculosis (TB) is gaining traction but faces significant real-world challenges in implementation, such as software setup, integration into workflows, network connectivity issues, and a shortage of healthcare personnel. To tackle these issues, PATH initiated a TB screening program in Nagpur, India, utilizing qXR, an AI software tool, across eight private CXR labs that met specific technical prerequisites. The program revealed valuable insights into the operational feasibility of AI deployment in resource-limited settings, highlighting the strategies needed to overcome logistical hurdles.

Throughout the <a href="https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000404">program</a>, 10,481 individuals were screened based on clinical history, resulting in 2,303 flagged as presumptive TB cases by either AI or radiologists. Thanks to AI, there was a 15.8% increase in TB case detection compared to traditional screening methods alone. This increase underscored the effectiveness of AI as a complementary diagnostic tool, especially in settings with limited healthcare resources.

TB continues to be a major public health issue in India, which reports nearly a third of the world’s TB cases. With India’s goal to eliminate TB by 2025, innovative approaches to diagnostics and patient care are crucial. Although CXRs are a recommended screening tool in India, limitations in resources—such as a shortage of radiologists—make consistent implementation difficult. AI solutions like qXR from Qure.ai, designed to assist in identifying TB signs in CXR images, offer promise but must overcome practical barriers in integration and use in diverse healthcare settings.

The Nagpur screening program encountered several technical and operational challenges that were addressed through strategic adaptations. Basic infrastructure, including internet access and compatible systems, proved critical for smooth AI software installation and operation. Initial reluctance from local radiology associations, driven by unfamiliarity with AI, was overcome through educational sessions, transparency, and consistent engagement with stakeholders, which ultimately built trust and acceptance of the new technology. Additionally, flexible technical setups allowed labs to address privacy concerns while accommodating AI functionality. By working closely with local partners, PATH was able to implement qXR in a way that respected the needs and limitations of each lab, leading to improved screening outcomes.

Overall, the increased TB detection rate achieved through the use of AI screening underscores the potential of AI-based tools to transform TB screening in India and other high-burden areas. However, broader deployment of these tools will require carefully designed solutions to address the real-world challenges of workflow integration, infrastructure compatibility, and stakeholder acceptance. This experience shows that with the right approach, AI can be a powerful asset in advancing TB care, particularly in resource-constrained environments.

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Introducing AI Toolkit: Simplifying AI deployments for TB Programs

No country aspires to be known for a high tuberculosis infection rate. But, unfortunately, Nigeria’s tuberculosis numbers are soaring rapidly, ranking third in the world, only behind India and China. Annually, the West African nation sees 590,000 new tuberculosis cases, and 245,000 Nigerians die of the disease every year.&nbsp;&nbsp;&nbsp;

Tuberculosis places an enormous burden on Nigeria’s public health system. Recognizing this, the National Tuberculosis and Leprosy Control Programme (NTBLCP) was set up in 1989. Multiple strategies have been implemented at the community and facility levels in public and private healthcare units. However, the system has yet to overcome the hurdles of low population coverage, lack of accessibility, inadequate resources, and delay in treatment.&nbsp;&nbsp;&nbsp;

Qure.ai, Fujifilm, and Omnia Health came together to organize a webinar on&nbsp;“Accelerating TB screening in rural communities using AI-powered technology."&nbsp;The aim was to capture how the three organizations had come together to use technology for Active case finding and how they are making a difference in the lives of people in rural Africa.&nbsp;&nbsp;&nbsp;

The distinguished panel of global speakers shared their experiences deploying mobile health tech and AI in parts of rural Nigeria struggling with little healthcare access.&nbsp;&nbsp;

The recent partnership between the Institute of Human Virology in Nigeria (IHVN), Fujifilm Healthcare Middle East &amp; Africa, and Qure.ai has been an innovative game-changer in the fight against tuberculosis.&nbsp;&nbsp;

Dr. Ronke Vivian Agbaje explained the problem –&nbsp;“In the past, our efficiency targets were not being met. We had partners who have worked with AI, and it has worked for them. So, we got four portable X-ray machines integrated AI. It improved our efficiency. We can now target our screenings better, and access has improved. We have also been able to detect other lung health issues in our patients, apart from TB."&nbsp;

According to Dr. Shibu Vijayan of Qure.ai- “The transmission chain is being cut via the usage of AI. Partnerships like this are critical to achieving the Global TB Target. Post-pandemic, technology is bridging the gap, and this partnership will ensure we achieve it humanely and cost-effectively. The efficiency brought in by AI for time, resources, and the cost is unmatched by other strategies implemented in the past."&nbsp;qXR's prowess lies in its ability to detect and identify 30 distinct findings in a chest X-ray and monitor the rate of disease progression. In addition, it has been CE-certified and FDA-approved, and independent studies by the World Health Organization (WHO) have validated Qure's solutions.&nbsp;&nbsp;&nbsp;

This partnership undoubtedly brings excellent value to Nigeria’s public health setup. Leveraging the portability of the handheld digital X-ray machine can bring the health system to the patient, who can then be diagnosed at the point of care. This eases the patient's mobility and connects them to the treatment pathway faster. In addition, mass testing and active screening expedite tuberculosis detection, treatment, and notification.&nbsp;

Within Nigeria, the Xair device embedded with the qXR AI solution has been deployed in twelve states, covering rural areas and vulnerable communities. Dr.&nbsp;Bethrand&nbsp;Odume said,&nbsp;“The resources are minimal. We are using this to do screenings in prisons. We can take it to the doorsteps of patients, and that plays a big role in bridging the gap in healthcare."&nbsp;

Besides providing accurate diagnosis of chest abnormalities, Qure’s AI solution reduces the disease’s reporting turnaround time to less than one minute. This assists radiologists in reducing their workload and gives them room to connect to other radiologists for discussion or review. Moreover, qXR minimizes the need for confirmatory tests like CBNAAT or sputum tests.&nbsp;&nbsp;&nbsp;

One of the reasons for this efficiency is the opportunity for early diagnosis that AI screening enables. Before disease manifestation, the algorithm can pick up on abnormalities and reduce tuberculosis’s communicability and transmission. Furthermore, by carefully mapping the hotspot areas within the country, they can do targeted screening within the population and increase coverage. As simple as it may sound, this creates a revolutionary push to improve the overall lung health of people.&nbsp;&nbsp;&nbsp;

“There is a huge gap around trained manpower across the world. We are still fighting against TB. Africa's Fujifilm and Qure.ai association is a good example of how a large corporation and a startup can make a difference. A product innovator can join hands with a corporate that now wants to spend a lot of time on innovation. And it makes a big synergetic impact. It is impactful in private healthcare as well,"&nbsp;said Naresh Hasija.&nbsp;&nbsp;&nbsp;

“It has been phenomenal to see how much impact AI can make. Fujifilm can provide a portable x-ray device embedded with this AI. Qure.ai is a peer-reviewed solution. We are now able to see this partnership evolve. It is being applied in rural communities, and the plan is to increase access and proximity to these devices. Being able to provide more devices to more people will be our future,"&nbsp;shared Godspower Asika.&nbsp;&nbsp;&nbsp;

At the root of every public health strategy implementation is the drive to make the system efficient, patient-oriented, and accessible without compromising quality. A competent patient management system integrated with innovative solutions can significantly accelerate the population's health goals. Qure.ai's partnership with Fujifilm and IHVN is a testament to these aims, making a significant difference in the fight against the tuberculosis epidemic.&nbsp;

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Accelerating TB screening in rural communities using AI-powered technology

The Philippines has long been at the forefront of the fight against tuberculosis (TB), with the Philippine Business for Social Progress (PBSP) playing a key role in TB control management for over two decades. The Advancing Client-centered Care and Expanding Sustainable Services for TB (ACCESS TB) project, funded by The Global Fund to Fight Aids, Tuberculosis, and Malaria, aims to further reduce TB prevalence, incidence, and mortality by providing comprehensive quality TB care to Filipinos.

A crucial component of the ACCESS TB project was the deployment of mobile vans equipped with X-ray machines and AI-enabled software for the interpretation of chest radiographs. These vans, manned by trained radiographers and health workers, were intended to screen presumptive TB cases and individuals with high-risk factors by running them across different cities in the Philippines.

The ACCESS TB project has gone beyond just screening and diagnosis. It has also provided diagnostics and treatment services for both drug-susceptible and multidrug-resistant TB (MDR-TB) cases, expanding access to hundreds of MDR-TB diagnostic and treatment centers. The project has also engaged thousands of private doctors, trained thousands of healthcare providers, and cured thousands of patients through its comprehensive approach.

When the COVID-19 pandemic hit the Philippines, the National TB Control Program (NTP) had to act quickly to ensure that TB patients continued to access their lifesaving treatment. The ACCESS TB project, along with the NTP, WHO, USAID, and other partners, developed the National TB Adaptive Plan to maintain TB prevention, testing, and treatment even during the lockdowns.

One of the key innovations was the implementation of home-based treatment for drug-resistant TB (DR-TB) patients. Prior to COVID-19, these patients had to report to a facility every day to take their medications, leading to a high rate of loss to follow-up. With the adaptive plan, patients were allowed to take a month's worth of medications home, and healthcare workers conducted regular home visits to monitor their progress and collect sputum samples for laboratory follow-ups.

This shift to home-based treatment had a significant impact, reducing the loss to follow-up rate from 16% before COVID-19 to only 4% in 2020. The pandemic has accelerated the adoption of these patient-centric measures, which have proven to be effective in improving treatment adherence and outcomes.

The ACCESS TB project also expanded the role of its Specimen Transport Riders (STRiders) – motorcycle riders who not only transport sputum specimens to laboratories but also deliver medications from facilities to patients' homes. This integrated service has benefited both TB and HIV programs.

With the support of the Global Fund's COVID-19 Response Mechanism (C19RM) funding, the ACCESS TB project is now scaling up digital adherence tools, such as video observed therapy (VOT) and digital pill boxes, to further enhance patient support and monitoring. Additionally, the project is expanding the reach of mobile clinics that can perform on-site TB testing and screening, including at COVID-19 testing and vaccination sites, to ensure that no one is left behind in the fight against TB.

The Philippines' proactive response and the collaborative efforts of the NTP, PBSP, and their partners have demonstrated the resilience and adaptability of the country's TB control program in the face of the COVID-19 pandemic. By prioritizing patient-centered care and leveraging innovative technologies, the ACCESS TB project is making significant strides in improving TB outcomes and paving the way for a healthier future for the Filipino people.

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Tuberculosis Crisis in Philippines: The Mobile Radiology Answer

Lung cancer remains one of the most pressing challenges in modern healthcare, being the leading cause of cancer mortality in the UK with approximately 47,000 new diagnoses each year. What's particularly concerning is that over a third of these patients are diagnosed only after presenting as emergency cases - often at late stages when treatment options are limited. Dr. Indrajeet Das, a consultant radiologist at the University of Leicester Hospital, recently shared insights into how artificial intelligence could transform lung cancer pathways and potentially save lives through earlier detection.

The current situation is sobering: patients presenting as emergencies are five times more likely to die within a year compared to those referred through primary care. This stark difference underscores the critical importance of early diagnosis. However, several challenges stand in the way of improving detection rates.

The UK faces a significant shortage of radiologists, with one of the lowest numbers of specialists per 100,000 people in the European Union. This shortage has led many hospitals, including Leicester, to outsource up to 60% of their X-ray reporting. While outsourcing helps manage workflow, ideally hospitals would prefer to keep abnormal cases in-house for faster response and better continuity of care.

This is where AI enters the picture. Dr. Das and his team have been exploring how AI tools could help triage chest X-rays, distinguishing between normal and abnormal cases to ensure the most critical cases receive immediate attention. However, Dr. Das emphasizes that AI alone isn't enough - it needs to be integrated into a comprehensive, streamlined pathway for patient care.

The Leicester team developed an innovative "straight to CT" pathway, where chest X-rays showing suspected lung cancer are fast-tracked. Patients receive early morning CT scans that are immediately reported, allowing for rapid assessment and intervention if needed. This approach has already shown promising results, with a 25% relative reduction in emergency presentations despite an increase in overall lung cancer diagnoses.

To validate the potential of AI in this pathway, Dr. Das's team partnered with Qure.ai, conducting a retrospective analysis of 1,448 GP-referred X-rays. The results were impressive: the AI system showed excellent ability to detect abnormalities and correctly identified eight out of ten confirmed lung cancer cases. While it missed two subtle cases, the system's performance suggested it could be valuable as a prioritization tool.

The success of this initial validation has led to a larger multi-center study funded by SBRI (Small Business Research Initiative), involving several leading UK hospitals. The goal is to achieve the ambitious target of reporting all routine or urgent chest X-rays within 24 hours, potentially revolutionizing the speed of lung cancer diagnosis.

What makes this approach particularly promising is its holistic nature. Rather than simply deploying AI as a standalone solution, the Leicester team has focused on integrating it into a comprehensive pathway that includes rapid CT scanning, expert reporting, and prompt clinical assessment. This integrated approach addresses not just the initial detection but the entire patient journey.

While some radiologists remain skeptical about AI's role in healthcare, the early results from Leicester suggest that when properly implemented as part of a well-designed pathway, AI tools can help address the critical challenges of radiologist shortages while potentially improving patient outcomes through earlier detection and treatment of lung cancer.

As we await the results of larger prospective trials, one thing is clear: the future of lung cancer detection likely lies in the thoughtful integration of AI tools with streamlined clinical pathways, supported by dedicated healthcare professionals working together to catch cancer earlier and save more lives.

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Determining the Value of AI in Lung Cancer Pathways | Dr Indrajeet Das, Leicester NHS Trust

The impact of AI at The Royal Bolton NHS Hospital, UK&nbsp;

Royal Bolton Hospital, part of Bolton NHS Foundation Trust, was the first NHS trust to adopt radiology AI, deploying Qure’s qXR solution in April 2020.&nbsp;&nbsp;

It was the height of the COVID-19 pandemic with the hospital experiencing a heavy footfall of symptomatic patients. qXR was used by both clinicians and radiologists for the reporting of chest X-rays as a second read to ensure no potential cases were missed and to support clinical decision-making for better patient outcomes.&nbsp;

The Royal Bolton Hospital in Farnworth, Greater Manchester is home to Bolton NHS Foundation Trust, providing healthcare services for people in the Metropolitan Borough of Bolton and the surrounding areas. The Trust was the first in the UK to deploy qXR, an imaging interpretation tool developed by Qure.ai, to help medical staff effectively monitor the extent and progression rate of COVID-19 in patients through the automated analysis of chest X-rays.&nbsp;

The initial months of 2020 saw an alarming spike of COVID-19 cases in the UK. It resulted in an immediate impact on the NHS, medical and social care systems as they faced the challenge of ensuring adequate testing. Patients suffering from the illness placed unprecedented demands on acute care services, particularly on intensive care units (ICUs) and the already burdened medical workforce. This resulted in a substantial rise in mortality rates.&nbsp;

As in other parts of the UK, Bolton faced an influx of COVID-19 patients and needed a system in place to improve efficiency in prognosis and alleviate the workload of the hospital staff.&nbsp;&nbsp;

COVID-19 clinically presents itself as consolidation, which are accumulations of fluid and/or tissue in pulmonary alveoli preventing gas exchange or ground-glass opacity, and through nodular shadowing. It primarily affects peripheral and lower areas of the lungs.&nbsp;

Qure’s deep learning-based automated chest X-ray interpretation platform – qXR – can detect, localise, and quantify a total of 29 findings, including COVID-19 related lesions. It had been trained and tested using a growing database of X-rays from diverse sources.&nbsp;&nbsp;

The solution gave 91% sensitivity and 77% specificity in predicting COVID-19 changes on chest X-rays. qXR could also monitor the extent and rate of progression of the infection, creating graphs showing the percentage area of lung affected and tracking changes on subsequent X-rays.&nbsp;

During the peaks of the pandemic, when PCR testing turnaround time was more than 24 hours, NHS clinicians relied on qXR to interpret chest X-rays reviews for the rapid assessment and triage patients into high, medium and low priority categories.&nbsp;&nbsp;

qXR gave almost instantaneous feedback to clinicians, providing out-of-hours clinical decision support and assisting accurate evaluation by clinicians with less expertise in chest X-ray reviews. By providing workflow support to improve efficiency and increase reporting capacity, qXR can also helped mitigate any shortage of trained radiologists.&nbsp;

Bolton NHS Foundation Trust had been exploring the use and potential benefits of AI in support of medical diagnoses and treatments for a considerable amount of time. However, the COVID-19 pandemic accelerated this process and resulted in the collaboration with Qure.ai.&nbsp;&nbsp;

Deploying qXR in the field of radiography helped the hospital staff manage the diagnosis and treatment of patients and also established the hospital’s reputation as a leader and pioneer in the development of the use of AI as part of clinical workflow.&nbsp;&nbsp;

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The impact of AI at The Royal Bolton NHS Hospital, UK

Dr. Indrajeet Das, a consultant radiologist at the University Hospitals of Leicester NHS Trust, recently shared his insights on the transformative role of artificial intelligence (AI) in radiology and patient care. As part of one of the UK’s largest acute healthcare providers, his work covers a wide range of areas, including respiratory and cardiac imaging, serving a population nearing one million across Leicester and Rutland. Leicester’s NHS Trust also functions as a key referral and research center, especially in cancer and cardiovascular services, which puts Dr. Das at the forefront of integrating new technologies like AI in clinical practice.

Dr. Das discussed how AI is shaping a new era in radiology, especially with tools like Qure.ai’s qXR, an AI application designed to interpret chest X-rays for various conditions, including lung cancer. He described AI’s progression as “an exciting revolution,” and while the technology is still in its early stages in Leicester, there is great promise. Dr. Das emphasized the importance of using AI in clinical trials that offer real-world evidence, explaining how collaboration with technology partners like Qure.ai helps refine AI’s effectiveness in clinical settings.

One of the critical initiatives discussed was the National Lung Cancer Optimal Pathway, which aims to significantly reduce the time between diagnosis and treatment of lung cancer. Dr. Das pointed out that early detection can often make the difference in outcomes, particularly in a disease with notoriously late-stage symptoms. The pathway initiative seeks to cut diagnosis times from an average of 62 days to under 49 days. To achieve this, the pathway recommends that chest X-rays suspected of showing lung cancer be reviewed within 24 hours, followed by a CT scan within 72 hours. Dr. Das suggested that implementing AI in radiology could help meet these tight deadlines, accelerating the diagnostic process and improving outcomes.

Reflecting on his early experience with qXR, Dr. Das mentioned a retrospective study of around 1,000 chest X-rays, where qXR demonstrated high specificity and sensitivity. The AI tool quickly flagged eight out of ten confirmed lung cancer cases, pinpointing their location accurately and performing faster than traditional reporting methods. He noted that had qXR been used in real-time, it could have expedited reporting and potentially led to quicker intervention.

Dr. Das is optimistic about the future of AI in the NHS, not only for cancer detection but also for conditions like tuberculosis, pneumothorax, and trauma injuries. He believes that AI can play a critical role in flagging urgent cases, helping radiologists prioritize cases when resources are stretched. This prioritization could improve patient outcomes by ensuring those in most critical need are attended to sooner.

For colleagues hesitant about AI, Dr. Das reassured that AI isn’t intended to replace radiologists but rather to support them, much like a car’s lane-keeping feature prevents accidents without taking over the driver’s role. He sees AI as a safety net that enhances diagnostic accuracy and efficiency, supporting radiologists by catching potential issues and allowing them to focus more effectively on complex cases. He is hopeful that with adequate governance, data protection, and research, AI could evolve into a new standard of care, offering a transformative tool for the healthcare system.

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