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Fourth, two researchers (T Sakamoto and YH) independently determined whether the final diagnosis was included within the AI-generated list of differential diagnoses; any inconsistencies were resolved by discussion. The accuracy of the AI differential diagnosis list was 172/381 (45.1%). Fifth, two researchers (T Sakamoto and YH) independently classified the commonality of the final diagnosis (common or uncommon disease) and the typicality of the clinical presentation (typical or atypical presentation).
JMIR Form Res 2024;8:e58666
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We used our data set from a previous study (TH, YH, KM, T Sakamoto, KT, T Shimizu. Diagnostic performance of generative artificial intelligences for a series of complex case reports. unpublished data, November 2023). From the Pub Med search, we identified a total of 557 case reports. We excluded the nondiagnosed cases (130 cases) and the pediatric cases, aged younger than 10 years (35 cases). The exclusion criteria were based on the previous research for CDSS [31].
JMIR Form Res 2024;8:e59267
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Final diagnoses were further categorized into common or uncommon diagnoses based on whether the incidence was more than 1 in 2000 (common disease) or not (uncommon disease) [33]; unclear cases were judged by 2 researchers (YH and T Sakamoto) through discussion. According to the final diagnosis and medical history created by the AI-based symptom checker, 2 researchers (YH and T Sakamoto) independently judged all cases as typical or atypical, and conflicts were resolved by discussion.
JMIR Form Res 2024;8:e53985
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Treatments for Trauma-Induced Coagulopathy: Protocol for a Systematic Review and Meta-Analysis
JMIR Res Protoc 2023;12:e49582
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Second, the other research physicians (T Sakamoto and ST) independently developed 2 additional DDx lists (the second and third lists) per case using 2 DDx generators (Isabel Pro and the AI diagnostic support system for general internal medicine) based on the patient’s age, sex, and medical history generated by the AI-driven automated medical history–taking system without reading the index lists generated by the AI-driven automated medical history–taking system.
JMIR Form Res 2023;7:e49034
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