Transforming radiology with AI-based diagnostics

The integration of artificial intelligence in healthcare, particularly in radiology, is changing diagnostic paradigms. Companies like Arterys, DeepMind (which was acquired by Google), and Cleerly are finding new and creative ways to employ AI for more streamlined and accurate health outcomes. One such company, Qure.ai, is developing AI-based tools that increase the speed and accuracy of diagnoses, reducing the burden on radiologists and improving patient outcomes.

As AI becomes more ingrained in medical workflows, its potential to revolutionize the healthcare industry grows, especially in resource-limited areas where access to radiologists is scarce.

The Role of AI in Medical Imaging

At the heart of Qure.ai’s innovation is its ability to process millions of medical images, significantly speeding up diagnostic processes. With its deep learning models, AI can analyze chest x-rays, CT scans and MRIs for diseases such as tuberculosis, lung cancer and stroke. AI has the ability to interpret these images autonomously, particularly in TB screenings, allowing doctors to make quick decisions without the need for radiologist intervention in many cases.

This capacity is crucial in regions with limited healthcare resources. In areas where TB is endemic, AI tools are implemented to quickly identify cases that require further testing. As Prashant Warier, co-founder and CEO of Qure.ai, explained in a recent interview, the AI ​​system deployed in mobile vans in the Philippines reduced the wait time for TB diagnosis from several weeks to just 30 seconds. The technology has been implemented in more than 3,000 locations worldwide, demonstrating its scalability and impact.

Advancing accuracy and speed in diagnoses

The success of AI in radiology is not just in its ability to process data quickly; it also improves diagnostic accuracy. Studies show that Qure.ai’s AI can perform as well as or better than human radiologists in some diagnostic tasks.

Warier explained: “What we’ve seen is that there are studies that show that if two radiologists report on the same chest X-ray, they will only agree 65% of the time. So 35% of the time they don’t agree on what’s on the X-ray, and that’s where the AI ​​will always agree. The AI ​​will always provide the same output for that X-ray. So consistency is very important.”

This consistency ensures that patients receive more reliable diagnoses, which is particularly critical for diseases that require timely interventions, such as lung cancer and stroke. For lung cancer, early detection can make a significant difference in patient outcomes. Qure.ai’s AI tools, in partnership with AstraZeneca, analyze routine chest x-rays to detect nodules and assess risks of malignancy, often flagging potential cases that might otherwise go unnoticed. This triage capability can help doctors prioritize high-risk patients and expedite treatment.

Global reach and impact

Qure.ai’s technology is not limited to a single region or market; is deployed globally in more than 90 countries. From mobile TB screening vans in the Philippines to partnerships with pharmaceutical giants like AstraZeneca for lung cancer detection, Qure.ai is making AI-powered healthcare accessible to underserved populations. With more than 10 million scans processed annually, its AI-based diagnostics are quickly becoming a cornerstone of global healthcare.

The company recently raised $65 million in Series D funding, which saw participation from new strategic and financial investors led by Lightspeed and 360 ONE Asset, joined by Merck Global Health Innovation Fund and Kae Capital. Existing investors also participated in the round, including Novo Holdings, Health Quad and TeamFund. With the new funding, the focus remains on expanding its AI models and expanding operations into new markets like the US. This funding will also allow the company to invest in fundamental AI models that enhance diagnostic capabilities, further improving speed, accuracy and scalability across various healthcare environments.

The future of AI in healthcare

Qure.ai’s technology reflects the beginning of a broader trend in healthcare where AI plays a key role not only in diagnosis, but also in treatment planning and patient management. The company’s next focus will likely involve integrating AI with other data sources, such as genomics and electronic medical records, to provide a more comprehensive view of a patient’s health. In doing so, AI can move beyond isolated diagnostic tasks and deliver more personalized and predictive care.

Warier believes that AI in healthcare is still at an early stage, but the potential is vast. “We are starting to integrate multiple data points to create more holistic AI models,” he explained. This change will allow doctors to make more informed decisions by considering a patient’s complete medical history along with diagnostic imaging.