지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
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초록· 키워드
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Objective: This study examined the efficacy of artificial intelligence (AI) algorithm-based diagnostic assistant solutions in the interpretation of brain computed tomography (CT) by emergency medicine (EM) residents.
Methods: This study included 350 patients who visited a local emergency medical center over 5 months and underwent brain CT scans. EM residents initially interpreted the patients’ scans. A second interpretation was performed using an AI algorithm-based solution. The initial and second interpretations were compared with that of a radiology physician.
Results: The first interpretation by EM residents showed agreement in 318 cases (90.9%), while the second, assisted by an AI algorithm-based solution, showed agreement in 308 cases (88.0%). The first interpretation had an accuracy, sensitivity, and specificity of 93.1%, 43.9%, and 99.7%, respectively, and the second had an accuracy, sensitivity, and specificity of 92.0%, 39.0%, and 99.0%, respectively (P<0.001). Most of the discrepancies observed in the first and second interpretations were classified as Grade 1.
Conclusion: The interpretations assisted by the AI algorithm-based solution resulted in lower accuracy and higher discrepancy rates than independent interpretations by EM residents. The AI algorithm-based solution provided efficacy in accurate interpretation depending on the cases. Further study will be needed to address the weaknesses of the function and utility of AI.
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