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Updated: Jun 21, 2026

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从数字化乳腺癌组织学幻灯片对转移性复发风险的深度学习评估

I Garberis1, V Gaury2, C Saillard2

  • 1INSERM U981, Gustave Roussy, Paris-Saclay University, Villejuif, France. ingrid-judith.GARBERIS@gustaveroussy.fr.

Nature communications
|July 2, 2025
PubMed
概括

一个人工智能工具RlapsRisk BC准确地预测早期乳腺癌患者的无转移生存率. 这种人工智能模型改善了风险分层,超出了传统方法,以更好地做出治疗决策.

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相关概念视频

Mouse Models of Cancer Study02:43

Mouse Models of Cancer Study

Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...
Mouse Models of Cancer Study02:43

Mouse Models of Cancer Study

Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...