Development, validation, and clinical evaluation of a machine-learning based model for diagnosing early infection after cardiovascular surgery (DEICS): a multi-center cohort study
The successful implementation of the XGBoost model facilitates accurate EPI diagnosis, improves postoperative recovery, and lowers hospital costs.
Authors
- Xiaoting Wu (ORCID: https://orcid.org/0000-0002-3996-868X)
- Dongjin Wang (ORCID: https://orcid.org/0000-0001-6499-1972)
- T. Zhu
- Ya-Xuan Gao
- Guo-Liang Fan
- Yu-Xian Tang
- Fu-Dong Fan
- Qing Zhou (ORCID: https://orcid.org/0000-0003-2316-5505)
- Tuo Pan
- Chuangshi Wang
- Jun Pan (ORCID: https://orcid.org/0000-0003-0161-9465)
- Xiateke Hafu
- Yusanjian Matniyaz
- Wei Wang (ORCID: https://orcid.org/0000-0003-0759-7332)
- He Zhang (ORCID: https://orcid.org/0000-0001-9198-6503)
- Yang Li (ORCID: https://orcid.org/0000-0002-4549-7087)
- Hai‐Tao Zhang (ORCID: https://orcid.org/0009-0001-3305-5767)
- Bian Wen
- Yuan-Xi Luo
- Xiang Li (ORCID: https://orcid.org/0000-0003-1465-8631)
- Wen Jiang (ORCID: https://orcid.org/0000-0003-0612-2917)
- Wenzhe Wang (ORCID: https://orcid.org/0000-0003-2378-0540)
- Yapeng Wang (ORCID: https://orcid.org/0000-0001-6317-9181)
- Hanghang Wang (ORCID: https://orcid.org/0000-0002-0360-7428)
- Zhiwei Fan (ORCID: https://orcid.org/0000-0002-8547-8593)
- Chen Li (ORCID: https://orcid.org/0009-0002-8030-8007)
- Zhi-Kang Lv
- Hao-Dong Pan
- Linshan Yang
- Zhi-Zhao Song
- Yunxing Xue
- Shi-Yu Guan
- B Zhang
- Qiang Wang (ORCID: https://orcid.org/0000-0002-1219-7889)
Institutions
- Boston University (US)
- Nanjing University of Chinese Medicine (CN)
- Harvard University (US)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- XinHua Hospital (CN)
- Massachusetts General Hospital (US)
- Nanjing Drum Tower Hospital (CN)
- Shanghai East Hospital (CN)
- First Bethune Hospital of Jilin University (CN)
- Johns Hopkins Hospital (US)
- Yangzhou University (CN)
Publication Details
- Journal
- International Journal of Surgery
- Published
- 2025-02-04
- DOI
- https://doi.org/10.1097/js9.0000000000002287
- Citations
- 5
- Primary Topic
- Bacterial Identification and Susceptibility Testing
- Type
- article
- Field-Weighted Citation Impact
- 6.59