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Perspective

A Perspective from a Case Conference on Comparing the Diagnostic Process: Human Diagnostic Thinking vs. Artificial Intelligence (AI) Decision Support Tools

1
Department of General Medicine, Showa University Koto Toyosu Hospital, Tokyo 135-8577, Japan
2
Department of Diagnostic and Generalist Medicine, Dokkyo Medical University Hospital, Tochigi 321-0293, Japan
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Department of Internal Medicine, Itabashi Chuo Medical Center, Tokyo 174-0051, Japan
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Division of Rheumatology, JR Tokyo Hospital, Tokyo 151-8528, Japan
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Department of General Medicine, Nerima Hikarigaoka Hospital, Tokyo 179-0072, Japan
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Department of Respiratory Medicine, JCHO Tokyo Shinjuku Medical Center, Tokyo 162-8543, Japan
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Department of Infection Control and Prevention, Nippon Medical School Hospital, Tokyo 113-8602, Japan
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Division of Emergency and General Medicine, Tokyo Metropolitan Tama Medical Center, Tokyo 183-8524, Japan
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2020, 17(17), 6110; https://doi.org/10.3390/ijerph17176110
Received: 24 July 2020 / Revised: 8 August 2020 / Accepted: 9 August 2020 / Published: 22 August 2020
Artificial intelligence (AI) has made great contributions to the healthcare industry. However, its effect on medical diagnosis has not been well explored. Here, we examined a trial comparing the thinking process between a computer and a master in diagnosis at a clinical conference in Japan, with a focus on general diagnosis. Consequently, not only was AI unable to exhibit its thinking process, it also failed to include the final diagnosis. The following issues were highlighted: (1) input information to AI could not be weighted in order of importance for diagnosis; (2) AI could not deal with comorbidities (see Hickam’s dictum); (3) AI was unable to consider the timeline of the illness (depending on the tool); (4) AI was unable to consider patient context; (5) AI could not obtain input information by themselves. This comparison of the thinking process uncovered a future perspective on the use of diagnostic support tools. View Full-Text
Keywords: artificial intelligence; decision support tool; diagnostic process artificial intelligence; decision support tool; diagnostic process
MDPI and ACS Style

Harada, T.; Shimizu, T.; Kaji, Y.; Suyama, Y.; Matsumoto, T.; Kosaka, C.; Shimizu, H.; Nei, T.; Watanuki, S. A Perspective from a Case Conference on Comparing the Diagnostic Process: Human Diagnostic Thinking vs. Artificial Intelligence (AI) Decision Support Tools. Int. J. Environ. Res. Public Health 2020, 17, 6110. https://doi.org/10.3390/ijerph17176110

AMA Style

Harada T, Shimizu T, Kaji Y, Suyama Y, Matsumoto T, Kosaka C, Shimizu H, Nei T, Watanuki S. A Perspective from a Case Conference on Comparing the Diagnostic Process: Human Diagnostic Thinking vs. Artificial Intelligence (AI) Decision Support Tools. International Journal of Environmental Research and Public Health. 2020; 17(17):6110. https://doi.org/10.3390/ijerph17176110

Chicago/Turabian Style

Harada, Taku, Taro Shimizu, Yuki Kaji, Yasuhiro Suyama, Tomohiro Matsumoto, Chintaro Kosaka, Hidefumi Shimizu, Takatoshi Nei, and Satoshi Watanuki. 2020. "A Perspective from a Case Conference on Comparing the Diagnostic Process: Human Diagnostic Thinking vs. Artificial Intelligence (AI) Decision Support Tools" International Journal of Environmental Research and Public Health 17, no. 17: 6110. https://doi.org/10.3390/ijerph17176110

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