{"id":976,"date":"2024-12-02T00:00:00","date_gmt":"2024-12-02T00:00:00","guid":{"rendered":"https:\/\/www.lunit.io\/media-hub\/real-world-validation-lunit-ai-proven-successful-in-1-year-breast-cancer-screening-deployment\/"},"modified":"2025-10-31T16:04:25","modified_gmt":"2025-10-31T16:04:25","slug":"real-world-validation-lunit-ai-proven-successful-in-1-year-breast-cancer-screening-deployment","status":"publish","type":"media-hub","link":"https:\/\/www.lunit.io\/en\/media-hub\/real-world-validation-lunit-ai-proven-successful-in-1-year-breast-cancer-screening-deployment\/","title":{"rendered":"Real-World Validation: Lunit AI Proven Successful in 1-Year Breast Cancer Screening Deployment"},"content":{"rendered":"

Follow-up to ScreenTrustCAD presented at RSNA 2024 highlights 1-year post-AI adoption success in improving cancer detection, radiologist workload, and screening efficiency<\/strong><\/em><\/p>\n

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SEOUL, South Korea, December 2, 2024<\/strong>\u2014 Lunit (KRX:328130.KQ), a leading provider of AI-powered solutions for cancer diagnostics and therapeutics, unveiled follow-up findings from the groundbreaking ScreenTrustCAD trial at the Radiological Society of North America (RSNA) 2024 Annual Meeting. This study, conducted at Capio S:t G\u00f6ran Hospital in Sweden, reinforces the real-world impact of Lunit INSIGHT MMG, which has successfully replaced one of the two human readers in the hospital\u2019s double-reading breast cancer screening protocol.<\/p>\n

Theoriginal ScreenTrustCAD trial (2021\u20132022), published inThe Lancet Digital Health<\/a>,was the first prospective interventional study to demonstrate that AI could match or even surpass traditional two-radiologist systems. Building on these findings, the hospital fully integrated AI in mid-2023 and became the first in the world to implement AI as an independent reader, fully replacing one radiologist. The new analysis compares screening performance before and after AI adoption, offering real-world validation of Lunit INSIGHT MMG\u2019s clinical and operational benefits.<\/p>\n

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Real-World Results: Efficiency Gains and Enhanced Screening Metrics<\/strong><\/p>\n

The follow-up study analyzed screening metrics from two nine-month periods: July 2018\u2013March 2019 (pre-AI \/ pre-COVID) and July 2023\u2013March 2024 (post-AI implementation).<\/p>\n

Key findings include:<\/strong><\/p>\n

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