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India Today
01-05-2025
- Health
- India Today
AI spots lung cancer signs in 5 million people, enables early diagnosis
A new technology screened chest X-rays of 5 million people across 20 countries and successfully detected early signs of lung cancer using artificial AI algorithm, developed through a collaboration between AstraZeneca and Indian health-tech company analyed scans conducted in Asia, the Middle East, Africa, and Latin America - regions where access to advanced diagnostic tools is often a global biopharmaceutical company headquartered in the UK, is known for developing life-saving treatments in oncology, cardiovascular, and respiratory diseases. It partnered with to deploy AI tools in resource-constrained settings, making early cancer detection more accessible. The screening program used proprietary algorithm, qXR, which analysed chest X-rays to identify abnormalities, particularly high-risk lung nodules that could indicate early-stage AI then flagged these cases for follow-up diagnostic tests like CT scans. So far, nearly 50,000 people with suspected nodules have been referred for further testing, enabling earlier diagnosis and faster intervention."Reaching the five million scan milestone demonstrates the power of digital innovation in transforming cancer care. AI-enabled tools like qXR are proving to be a cost-effective way to screen for lung cancer where radiologists or advanced imaging facilities may not be readily available," said Ti Hwei How, Vice President of International Oncology at CEO Prashant Warier noted that this collaboration has helped scale their AI technology in real-world clinical environments. "This milestone shows how AI can bridge the gap in healthcare access and strengthen systems through faster diagnosis," he cancer remains the leading cause of cancer-related deaths worldwide, particularly in low- and middle-income countries. In these regions, where screening programs are often lacking, technology like qXR offers a promising way forward.A recent study presented at the European Lung Cancer Congress 2025 found that qXR successfully identified high-risk nodules in 54.1% of cases, highlighting its utility as a frontline screening this, AstraZeneca and are now working with local governments and health agencies to expand the reach of AI-powered screening and bring timely lung cancer diagnosis to even more underserved Watch
Time of India
01-05-2025
- Health
- Time of India
AstraZeneca's AI lung cancer screening program executes 5 mn tests, flags 50k individuals at high risk
New Delhi: UK pharma major AstraZeneca in partnership with health-tech company , announced the completion of 5 million artificial intelligence (AI) enabled chest X-rays (CXRs) across more than 20 countries in Asia, the Middle East, Africa, and Latin America. The screen program is part of the World Economic Forum 's EDISON alliance 1 Billion Lives Challenge and under its commitment AstraZeneca's aims to demonstrate the potential of AI in improving lung cancer detection , especially in resource-limited healthcare settings. Of the 5 million excluded by the partners the CXRs revealed important findings, including lung nodules at high risk for cancer in nearly 50,000 people who were later referred for further testing and possible diagnosis. 'With successful implementation in countries such as Colombia, El Salvador and India, we are setting the stage for scaling this approach. We are actively partnering with Ministries of Health and policymakers to prioritise lung health and lung cancer on national agendas, including through AI-enabled screening programs to make a real difference,' said Ti Hwei How, Vice President, International Oncology, AstraZeneca. In 2020, under the Network initiative, AstraZeneca partnered with to harness qXR® technology for assessing CXRs and determining potential lung cancer risk. As per the drug maker by using AI to analyse routine X-rays for risks of cancer, healthcare professionals can focus further assessment, such as a low-dose CT scan to confirm or rule out lung cancer and is especially helpful in countries where resources are limited, as it helps to make the best use of available equipment and expertise, ensuring that those at highest risk get the attention they need and that screening programs are as effective as possible.
