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.

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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
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article

Development, validation, and clinical evaluation of a machine-learning based model for diagnosing early infection after cardiovascular surgery (DEICS): a multi-center cohort study

Xiaoting Wu, Dongjin Wang, T. Zhu, Ya-Xuan Gao et al.
5 citations
International Journal of Surgery
Bacterial Identification and Susceptibility Testing
6.59
article

Development, validation, and clinical evaluation of a machine-learning based model for diagnosing early infection after cardiovascular surgery (DEICS): a multi-center cohort study

Xiaoting Wu, Dongjin Wang, T. Zhu, Ya-Xuan Gao, Guo-Liang Fan, Yu-Xian Tang, Fu-Dong Fan, Qing Zhou, Tuo Pan, Chuangshi Wang, Jun Pan, Xiateke Hafu, Yusanjian Matniyaz, Wei Wang, He Zhang, Yang Li, Hai‐Tao Zhang, Bian Wen, Yuan-Xi Luo, Xiang Li, Wen Jiang, Wenzhe Wang, Yapeng Wang, Hanghang Wang, Zhiwei Fan, Chen Li, Zhi-Kang Lv, Hao-Dong Pan, Linshan Yang, Zhi-Zhao Song, Yunxing Xue, Shi-Yu Guan, B Zhang, Qiang Wang
article en
5 citations

Abstract

The successful implementation of the XGBoost model facilitates accurate EPI diagnosis, improves postoperative recovery, and lowers hospital costs.

International Journal of SurgeryVol. 111(4)
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)
Openalex Percentile: Top 4%
Bacterial Identification and Susceptibility Testing
6.59
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