Explainable prediction of hypothermia risk in laparoscopic surgery: a retrospective cross-sectional study using machine learning
This study developed an efficient and interpretable predictive model for the risk of hypothermia in patients undergoing laparoscopic surgery. This model supports clinical decision-making and contributes to the overall goal of providing personalized care in the surgical environment.
Authors
- Jie Yu (ORCID: https://orcid.org/0000-0003-1393-4227)
- Huiyu Jia
- Shihong Dong
- Yingtao Meng (ORCID: https://orcid.org/0000-0002-2048-0334)
- Wenyu Su (ORCID: https://orcid.org/0000-0002-4857-8798)
- Wenjing Chang (ORCID: https://orcid.org/0000-0003-2036-0743)
- Shan Jiang (ORCID: https://orcid.org/0000-0003-2020-6447)
- Xiaoli Wang (ORCID: https://orcid.org/0000-0002-7198-273X)
- Guifeng Ma
- Huaiju Ge
Institutions
- Weifang Medical University (CN)
- Shandong First Medical University (CN)
- Shandong Center for Disease Control and Prevention (CN)
Publication Details
- Journal
- BMC Surgery
- Published
- 2025-10-03
- DOI
- https://doi.org/10.1186/s12893-025-03071-9
- Citations
- 1
- Primary Topic
- Thermal Regulation in Medicine
- Type
- article
- Field-Weighted Citation Impact
- 1.55
Funders
- Shandong First Medical University