Guardrails for the use of generalist AI in cancer care

IF 72.5 1区医学 Q1 ONCOLOGY

Nature Reviews Cancer Pub Date : 2024-04-16 DOI:10.1038/s41568-024-00685-8

Stephen Gilbert, Jakob Nikolas Kather

引用次数: 0

Abstract

Artificial narrow intelligence models, trained for specific intended purposes, have gained approval and recommendation for cancer treatment. Generalist medicial artificial intelligence (GMAI) models are now being developed for cancer treatment. Policy makers have a stark choice: radically adapt frameworks, block generalist approaches or force them onto narrower tracks. Generalist medical artificial intelligence (GMAI) models are gaining momentum in their applications for cancer treatment. In this Comment, Gilbert and Kather advocate for novel regulation of GMAI approaches to ensure patient safety and adequate physician support.

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在癌症护理中使用通用人工智能的指导原则

为特定目的而训练的人工狭义智能模型已被批准并推荐用于癌症治疗。目前正在开发用于癌症治疗的通用人工智能（GMAI）模型。政策制定者面临着一个严峻的选择：从根本上调整框架、阻止通用方法或迫使它们进入更狭窄的轨道。通用医学人工智能（GMAI）模型在癌症治疗领域的应用势头正猛。在这篇评论中，吉尔伯特和凯瑟主张对GMAI方法进行新的监管，以确保患者安全和医生的充分支持。

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

Nature Reviews Cancer 医学-肿瘤学

CiteScore

111.90

自引率

0.40%

发文量

审稿时长

6-12 weeks

期刊介绍： Nature Reviews Cancer, a part of the Nature Reviews portfolio of journals, aims to be the premier source of reviews and commentaries for the scientific communities it serves. The correct abbreviation for abstracting and indexing purposes is Nat. Rev. Cancer. The international standard serial numbers (ISSN) for Nature Reviews Cancer are 1474-175X (print) and 1474-1768 (online). Unlike other journals, Nature Reviews Cancer does not have an external editorial board. Instead, all editorial decisions are made by a team of full-time professional editors who are PhD-level scientists. The journal publishes Research Highlights, Comments, Reviews, and Perspectives relevant to cancer researchers, ensuring that the articles reach the widest possible audience due to their broad scope.