A systematic survey of computer-aided diagnosis in medicine: Past and present developments
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Models that may perform well during development can degrade in real-world settings due to dataset drift across diverse sites, devices, and populations.
“Models that may perform well during development can degrade in real-world settings due to dataset drift across diverse sites, devices, and populations15–18.”
From What the AI era doctor should know: a scoping review of proposed artificial intelligence competencies for medical education (2026) · cites this paper as [15]
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- Authors
- Yanase, J., & Triantaphyllou, E.
- Affiliations
- Louisiana State University (US)
- Corresponding author
- Triantaphyllou, Evangelos
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2019-12
- Volume
- 138
- Pages
- 112821
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2959687571
- Cited by
- 303
- References
- 265
- Citations by year
- 2026: 15 · 2025: 43 · 2024: 51 · 2023: 64 · 2022: 63 · 2021: 46 · 2020: 18 · 2019: 3
- FWCI
- 35.61
- Type
- journal article
- Language
- en
- Open access
- Locations
- Expert Systems with Applications (publishedVersion)
- Civil War Book Review (submittedVersion)
- Topics
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Technology and Human Factors in Education and Health
- Keywords
- computer-aided diagnosis, expert systems, intelligent systems, medical data processing, clinical decision-making
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