INCISIONAL HERNIA PREDICTION USING MACHINE LEARNING MODELS
收藏Mendeley Data2026-04-09 收录
下载链接：
https://data.mendeley.com/datasets/s5yws2pjkn
下载链接
链接失效反馈官方服务：
资源简介：
Retrospective cohort study type of diagnostic tests. Patients over 18 years of age who underwent midline laparotomy were included. The main outcome was the occurrence of IH. Three ML methods were evaluated: Logistic Regression, Decision Tree, and XGBoost. Each model's predictive capacity, Friedman range score, and clinical utility were assessed. The usefulness of all models was further evaluated using Bayes' theorem to determine the change in prevalence after applying the models.
提供机构：
Centro de Investigacion e Innovacion en Tecnologias de la Informacion y Comunicacion; Centro de Investigaciones en Optica AC; Centro de Investigacion en Ciencias de Informacion Geoespacial Ciudad de Mexico
