Confounders in developing a machine learning model for colorectal liver metastasis post-hepatectomy prognostications.

IF 6.1 2区医学 Q1 GASTROENTEROLOGY & HEPATOLOGY

Hepatobiliary surgery and nutrition Pub Date : 2024-04-03 Epub Date: 2024-01-10 DOI:10.21037/hbsn-23-546

Kin Pan Au, Tan To Cheung

引用次数: 0

查看原文本刊更多论文

为肝切除术后结直肠癌肝转移预后开发机器学习模型的干扰因素。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Hepatobiliary surgery and nutrition Multiple-

自引率

10.00%

发文量

392

期刊介绍： Hepatobiliary Surgery and Nutrition (HBSN) is a bi-monthly, open-access, peer-reviewed journal (Print ISSN: 2304-3881; Online ISSN: 2304-389X) since December 2012. The journal focuses on hepatopancreatobiliary disease and nutrition, aiming to present new findings and deliver up-to-date, practical information on diagnosis, prevention, and clinical investigations. Areas of interest cover surgical techniques, clinical and basic research, transplantation, therapies, NASH, NAFLD, targeted drugs, gut microbiota, metabolism, cancer immunity, genomics, and nutrition and dietetics. HBSN serves as a valuable resource for professionals seeking insights into diverse aspects of hepatobiliary surgery and nutrition.