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基因诊断和发现由大型语言模型实现
Tao Tu1, Khaled Saab1, Weida Liu2
1Google DeepMind, Mountain View, California, USA.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|February 8, 2026
概括
像Med-PaLM 2和Gemini这样的大型语言模型 (LLM) 可以加速遗传诊断和发现. 这些人工智能工具成功地确定了小鼠和人类的遗传因素,有助于诊断罕见疾病.
科学领域:
- 基因组学就是基因组学.
- 人工智能的人工智能
- 医学诊断 医学诊断 医学诊断
背景情况:
- 人工智能 (AI) 和大型语言模型 (LLM) 在临床应用中表现有前途.
- 对于LLM加速遗传诊断和发现的潜力仍然在很大程度上未被探索.
研究的目的:
- 评估LLM (Med-PaLM 2和Gemini) 在加速基因诊断和发现方面的能力.
- 为了评估在一系列遗传问题复杂性的LLM表现.
主要方法:
- Med-PaLM 2处理了自由文本输入,以确定生物医学特征的致病性小鼠基因.
- 为Gemini 2.5 Pro开发了一个检索和接地管道,以分析基因列表并确定人类听力损失的致病因素.
- 根据复杂的症状描述,Gemini 2.5 Pro被调整为识别罕见疾病的遗传因素.
主要成果:
- Med-PaLM 2准确地确定了已知的小鼠遗传因素和听力损失的新型因素.
- 双子座2.5 Pro成功协助识别导致人类听力损失和罕见遗传疾病的遗传因素.
- 人工智能管道在小鼠和人类遗传分析中都表现出有效性.
结论:
- 在动物模型和人类受试者中,LLM可以显著促进遗传诊断和发现.
- 人工智能驱动的管道显示出提高疾病遗传原因识别效率的潜力.
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