Validation of an acute kidney injury prediction model as a clinical decision support system
AKI predictions were enhanced by AI assistance, but the improvements varied according to the expertise of the user.
Authors
- Giae Yun (ORCID: https://orcid.org/0000-0003-3712-9011)
- Jaesik Choi (ORCID: https://orcid.org/0000-0002-4663-3263)
- Jinyeong Yi (ORCID: https://orcid.org/0000-0003-1478-1605)
- Sejoong Kim (ORCID: https://orcid.org/0000-0002-7238-9962)
- Ji Hyun Kim (ORCID: https://orcid.org/0000-0001-8477-0157)
- Hyunkyung Han (ORCID: https://orcid.org/0009-0006-2672-384X)
- Sun-Ho Han
- Jihyeon Seong (ORCID: https://orcid.org/0000-0002-3591-131X)
- Enver Menadjiev
Institutions
- Seoul National University of Science and Technology (KR)
- Seoul National University (KR)
- Korea Advanced Institute of Science and Technology (KR)
- Seoul National University Bundang Hospital (KR)
- Hallym University Dongtan Sacred Heart Hospital (KR)
Publication Details
- Journal
- Kidney Research and Clinical Practice
- Published
- 2025-01-09
- DOI
- https://doi.org/10.23876/j.krcp.24.163
- Primary Topic
- Autopsy Techniques and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Seoul National University Bundang Hospital
- Seoul National University
- Ministry of Science and ICT, South Korea
- Institute for Information and Communications Technology Promotion