Biao Chen, Weiyong Sheng, Zhixin Wu, Bingqing Ma, Nan Cao, Xushu Li, Jia Yang, Xiaowei Yuan, Lizhao Yan, Gaobo Zhu, Yuanhong Zhou, Zhonghua Huang, Meiwei Zhu, Xuehui Ding, Hansong Du, Yanqing Wan, Xuan Gao, Xing Cheng, Peng Xu, Teng Zhang, Kaixiong Tao, Xiaoming Shuai, Ping Cheng, Yong Gao, Jinxiang Zhang
BACKGROUND: Currently, there is a lack of ideal risk prediction tools in the field of emergency general surgery (EGS). The American Association for the Surgery of Trauma recommends developing risk assessment tools specifically for EGS-related diseases. In this study, we sought to utilize machine learning (ML) algorithms to explore and develop a web-based calculator for predicting five perioperative risk events of eight common operations in EGS. METHOD: This study focused on patients with EGS and utilized electronic medical record systems to obtain data retrospectively from five centers in China...
March 15, 2024: International Journal of Surgery