Liability scores for chronic obstructive pulmonary disease obtained from our deep learning model improve genetic association discovery and risk prediction. We trained our model using full spirograms and noisy medical record labels obtained from self-reporting and hospital diagnostic codes, and demonstrated that the machine-learning-based phenotyping approach can be generalized to diseases that lack expert-defined annotations.

中文翻译：

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深度学习模型改进了 COPD 风险预测和基因发现

从我们的深度学习模型中获得的慢性阻塞性肺疾病的责任评分改善了遗传关联发现和风险预测。我们使用完整的呼吸图和从自我报告和医院诊断代码中获得的嘈杂病历标签来训练我们的模型，并证明基于机器学习的表型分析方法可以推广到缺乏专家定义注释的疾病。