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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
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| 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
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| 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,
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Received: July 19, 2023; Revised: September 12, 2023 Accepted: October 11, 2023. Published online: April 30, 2024. |
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| 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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