Development and external validation of an artificial intelligence model for predicting mortality and prolonged ICU stay in postoperative critically ill patients: a retrospective study
This study represents a significant advancement in the application of AI in critical care, especially for postoperative critically ill patients. The developed AI model outperformed existing models in predicting mortality and prolonged ICU stay, demonstrating notable accuracy and reliability. Its ability to identify critical, under-emphasized clinical factors could enhance decision-making in critical care settings. Although promising, further validation in diverse clinical settings is essential to confirm the model's efficacy and broader applicability.
Authors
- Jae Young Moon (ORCID: https://orcid.org/0000-0001-8724-6289)
- Kyung Sook Hong (ORCID: https://orcid.org/0000-0002-8022-5693)
- Seung Min Baik (ORCID: https://orcid.org/0000-0003-1051-6775)
- Jae Gil Lee (ORCID: https://orcid.org/0000-0002-1148-8035)
- Hankuil Yi (ORCID: https://orcid.org/0000-0002-9951-7856)
- Dong Jin Park (ORCID: https://orcid.org/0000-0002-2412-5292)
Institutions
- Ewha Womans University (KR)
- Korea University (KR)
- The Catholic University of Korea Seoul St. Mary's Hospital (KR)
- Korea University (JP)
- Catholic University of Korea (KR)
Publication Details
- Journal
- World Journal of Emergency Surgery
- Published
- 2025-10-15
- DOI
- https://doi.org/10.1186/s13017-025-00650-2
- Citations
- 1
- Primary Topic
- Cardiac, Anesthesia and Surgical Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 1.39
Funders
- National Research Foundation
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea