A Clinician’s Guide to Understanding Bias in Critical Clinical Prediction Models

IF 3 3区医学 Q2 CRITICAL CARE MEDICINE

Critical Care Clinics Pub Date : 2024-08-30 DOI:10.1016/j.ccc.2024.05.011

João Matos MSc , Jack Gallifant MBBS, MSc , Anand Chowdhury MD, MMCi , Nicoleta Economou-Zavlanos PhD , Marie-Laure Charpignon MS , Judy Gichoya MD , Leo Anthony Celi MD, MS, MPH , Lama Nazer PharmD , Heather King PhD , An-Kwok Ian Wong MD, PhD

引用次数: 0

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了解关键临床预测模型偏差的临床医师指南》。

这篇叙述性综述重点探讨了临床预测模型在支持重症监护知情决策中的作用，强调了它们的两种形式：传统评分和基于人工智能（AI）的模型。作者承认这两种类型的模型都可能存在偏差，并强调了批判性评估对提高我们对模型的信任度的重要性。作者概述了管理人工智能模型偏差风险的建议和关键护理实例。作者主张加强对临床医生的跨学科培训，鼓励他们探索各种资源（书籍、期刊、新闻网站和社交媒体）和活动（数据马拉松），以加深对偏倚风险的理解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Critical Care Clinics 医学-危重病医学

CiteScore

8.00

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Critical Care Clinics updates you on the latest trends in patient management, keeps you up to date on the newest advances, and provides a sound basis for choosing treatment options. Published four times a year—in January, April, July, and October—each issue focuses on a single topic in critical care, including cardiac emergencies, sepsis, infectious diseases, shock and trauma, neurologic problems, toxicology, pulmonary disorders, intensive care procedures, and patient observation. Critical Care Clinics is also an ideal resource for those in the fields of anesthesia, emergency medicine, and respiratory medicine.