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J Korean Soc Emerg Med > Volume 35(2); 2024 > Article
Journal of The Korean Society of Emergency Medicine 2024;35(2): 165-174.
응급의학과 전공의의 brain CT 판독에 인공지능 알고리즘 기반 진단보조솔루션을 적용한 시도
김동억 , 서영우 , 고승현
대구가톨릭대학교 의과대학 응급의학교실
The trial of application for interpretation on brain computed tomography by emergency medicine residents assisted artificial intelligence algorithm-based solution
Dong Eok Kim , Young Woo Seo , Seung Hyun Ko
Department of Emergency Medicine, Daegu Catholic University School of Medicine, Daegu, Korea
Correspondence  Young Woo Seo ,Tel: 053-650-3061, Fax: 053-626-5307, Email: emseo@cu.ac.kr,
Received: July 19, 2023; Revised: September 12, 2023   Accepted: October 11, 2023.  Published online: April 30, 2024.
ABSTRACT
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.
Method:
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.
Key words: Computed tomography; Image interpretation; Emergencies; Artificial intelligence
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