Machine learning enhances assessment of proficiency in endovascular aortic repair simulations

IF 2.3 3区医学 Q2 SURGERY

Current Problems in Surgery Pub Date : 2024-08-02 DOI:10.1016/j.cpsurg.2024.101576

Rebecca Andrea Conradsen Skov MD , Jonathan Lawaetz MD, PhD , Michael Strøm MD, PhD , Isabelle Van Herzeele MD, PhD , Lars Konge MD, PhD , Timothy Andrew Resch MD, PhD , Jonas Peter Eiberg MD, PhD , ENHANCE research collaborators

引用次数: 0

查看原文本刊更多论文

机器学习增强了对血管内主动脉修复模拟熟练程度的评估

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

Current Problems in Surgery 医学-外科

CiteScore

5.20

自引率

0.00%

发文量

审稿时长

18 days

期刊介绍： Current Problems in Surgery keeps readers up-to-date on the latest surgical advances. Each month, this publication examines a single clinical problem or condition commonly seen by general surgeons. Issues also focus on topics in surgical research and emerging ideas in surgical subspecialties. Current Problems in Surgery is ideal for information too urgent to await book publication, yet too important to be summarized in a brief journal article.