人工智能可以准确识别肺癌组织学图像中的可靶向改变

IF 81.1 1区医学 Q1 ONCOLOGY

Nature Reviews Clinical Oncology Pub Date : 2025-02-10 DOI:10.1038/s41571-025-00999-y

Hortense Le, Aristotelis Tsirigos

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引用次数: 0

摘要

DeepGEM是一种基于人工智能（AI）的模型，可以准确预测肺癌患者样本制备的组织学切片中关键基因组改变的存在。这种方法为基因组检测提供了一种经济有效的替代方法，可以生成空间突变图，并可能支持个性化治疗策略。DeepGEM在不同的数据集上进行了验证，突显了人工智能在改变精准肿瘤学和改善全球医疗公平方面的潜力。

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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AI accurately identifies targetable alterations in lung cancer histological images

DeepGEM, an artificial intelligence (AI)-based model, accurately predicts the presence of key genomic alterations in histological slides prepared from samples obtained from patients with lung cancer. This approach provides a cost-effective alternative to genomic testing, generates spatial mutation maps and might support personalized treatment strategies. Validated in diverse datasets, DeepGEM highlights the potential of AI to transform precision oncology and improve global healthcare equity.

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来源期刊

Nature Reviews Clinical Oncology 医学-肿瘤学

CiteScore

99.40

自引率

0.40%

发文量

114

审稿时长

6-12 weeks

期刊介绍： Nature Reviews publishes clinical content authored by internationally renowned clinical academics and researchers, catering to readers in the medical sciences at postgraduate levels and beyond. Although targeted at practicing doctors, researchers, and academics within specific specialties, the aim is to ensure accessibility for readers across various medical disciplines. The journal features in-depth Reviews offering authoritative and current information, contextualizing topics within the history and development of a field. Perspectives, News & Views articles, and the Research Highlights section provide topical discussions, opinions, and filtered primary research from diverse medical journals.