Lunit Insight CXR (Photo by Lunit)

Lunit Insight CXR (Photo by Lunit)

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[Asia Economy Reporter Chunhee Lee] Medical artificial intelligence (AI) company Lunit announced on the 17th that its chest X-ray image analysis AI solution, 'Lunit Insight CXR,' demonstrated diagnostic accuracy comparable to that of radiologists with over 20 years of experience when applied in various medical environments.


This study was conducted jointly with the Medical Research Institute (QMRI) at the University of Edinburgh and the Royal Infirmary of Edinburgh in the UK. The research results were recently published in the international journal Clinical Radiology, issued by the Royal College of Radiologists (RCR) in the UK.


The research team applied Lunit Insight CXR to a total of 1,960 chest X-ray datasets showing 10 major lung diseases, including pneumonia, pulmonary fibrosis, and pneumothorax, and compared the results with those interpreted by radiologists. For this purpose, real-world data from primary care institutions and emergency rooms in the UK, consisting of 992 and 968 cases respectively, were utilized.


As a result, Lunit Insight CXR showed high accuracy with an average abnormal finding detection predictive power of 0.940 (range 0.881?0.999) in the AI model performance evaluation metric, the Area Under the ROC Curve (AUROC). The closer the AUROC is to 1, the more reliable the prediction is considered. The AUROC score of Lunit Insight CXR was similar to the diagnostic accuracy of radiologists with over 20 years of experience who participated in the study.


Edwin J.R. van Beek, professor of radiology at the University of Edinburgh Medical Research Institute and lead of the joint study, stated, "This study confirmed that Lunit's AI solution demonstrates high accuracy and has the potential to be reliably utilized in any medical setting." He added, "The AI solution will greatly help address the shortage of radiologists faced by Europe, including the UK."



Seobeom Seok, CEO of Lunit, also said, "Lunit Insight CXR provides accurate and rapid analysis results for lesions such as lung cancer, pneumonia, pneumothorax, and tuberculosis," adding, "We will strive to help doctors make precise and efficient diagnoses and significantly improve the shortage of radiologists."


This content was produced with the assistance of AI translation services.

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