Evaluation of Perioperative Cardiovascular Event Risk in Gastrointestinal Surgery ― Predictive Modeling and Risk Stratification Using Machine Learning ―
A machine learning model built from basic clinical information, comorbidities, and surgical information demonstrated the capacity to stratify MACE risk in patients undergoing gastrointestinal surgery.
Authors
- Tomohisa Seki
- Yoshimasa Kawazoe (ORCID: https://orcid.org/0000-0002-7277-0827)
- Hiromasa Ito (ORCID: https://orcid.org/0009-0003-8059-8857)
- Masafumi OKADA (ORCID: https://orcid.org/0000-0002-7715-5292)
- Kazuhiko Ohe (ORCID: https://orcid.org/0000-0002-4296-9536)
- Yu Akagi (ORCID: https://orcid.org/0000-0002-5724-7982)
- Kazumi Kubota
- Toru Takiguchi (ORCID: https://orcid.org/0000-0003-0824-6200)
- Kana Miyake
Institutions
- Mie University (JP)
- University of Tokyo Hospital (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- Circulation Journal
- Published
- 2025-04-23
- DOI
- https://doi.org/10.1253/circj.cj-25-0032
- Citations
- 2
- Primary Topic
- Cardiac, Anesthesia and Surgical Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 2.78
Funders
- Forskningsrådet om Hälsa, Arbetsliv och Välfärd