AI Helps Physicians Achieve Higher Diagnostic Accuracy in Interpreting Chest X-Rays

Now, a new study has found that AI-assisted CXR interpretation improves the diagnostic performance of non-radiologist physicians in detecting abnormal lung findings.

The study was conducted by researchers at the Konyang University School of Medicine (Daejeon, Korea) to investigate whether AI assistance improves the diagnostic performance of physicians for CXR interpretation and affects their clinical decisions in clinical practice. The researchers randomly allocated eligible patients who visited an outpatient clinic to the intervention (with AI-assisted interpretation) and control (without AI-assisted interpretation) groups. Lung lesions on CXR were recorded by seven non-radiologists with or without AI assistance. The reference standard for lung lesions was established by three radiologists. The primary and secondary endpoints were the physicians’ diagnostic accuracy and clinical decision, respectively.

Between October 2020 and May 2021, 162 and 161 patients were assigned to the intervention and control groups, respectively. The area under the receiver operating characteristic curve was significantly larger in the intervention group than in the control group for the CXR level and lung lesion level. The intervention group had higher sensitivity in terms of both CXR and lung lesion level and a lower false referral rate for the lung lesion level. AI-assisted CXR interpretation did not affect the physicians’ clinical decisions. Based on their study results, the researchers concluded that AI-assisted CXR interpretation improves the diagnostic performance of non-radiologist physicians in detecting abnormal lung findings.

“Physicians showed a better performance in [chest radiography] interpretation with AI assistance than without it,” stated Hyun Woo Lee, MD. “AI assistance allowed physicians to find more lung lesions.”

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Konyang University School of Medicine