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肝脏手术中的机器学习:益处与陷阱

Machine learning in liver surgery: Benefits and pitfalls.

作者信息

Calleja Rafael, Durán Manuel, Ayllón María Dolores, Ciria Ruben, Briceño Javier

机构信息

Hepatobiliary Surgery and Liver Transplantation Unit, Hospital Universitario Reina Sofía, Maimonides Biomedical Research Institute of Cordoba, Córdoba 14004, Spain.

出版信息

World J Clin Cases. 2024 Apr 26;12(12):2134-2137. doi: 10.12998/wjcc.v12.i12.2134.

Abstract

The application of machine learning (ML) algorithms in various fields of hepatology is an issue of interest. However, we must be cautious with the results. In this letter, based on a published ML prediction model for acute kidney injury after liver surgery, we discuss some limitations of ML models and how they may be addressed in the future. Although the future faces significant challenges, it also holds a great potential.

摘要

机器学习(ML)算法在肝病学各个领域的应用是一个备受关注的问题。然而,我们必须对结果持谨慎态度。在这封信中,基于已发表的肝切除术后急性肾损伤的ML预测模型,我们讨论了ML模型的一些局限性以及未来如何解决这些问题。尽管未来面临重大挑战,但也具有巨大潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2518/11045503/6608c01dd139/WJCC-12-2134-g001.jpg

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