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PREDICTION OF ADVERSE DRUG REACTION BASED ON MACHINE-LEARNED MODELS USING PROTEIN FUNCTION SCORES AND CLINICAL FACTORS
PREDICTION OF ADVERSE DRUG REACTION BASED ON MACHINE-LEARNED MODELS USING PROTEIN FUNCTION SCORES AND CLINICAL FACTORS
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机译:基于机器学习模型的不良药物反应预测使用蛋白质功能评分和临床因素
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摘要
The present disclosure predicts adverse reaction to drugs based on individual genetic and clinical information. The system receives as an input to the system gene sequence information and clinical information for a subject, and determines one or more scores (e.g., protein function score, clinical factor score, drug safety score) based on that information, where the scores can indicate subject's risk of having the adverse drug reaction. The system provides a representation of the prediction and/or information about the associated phenotype for display on a user interface in a client device (e.g., a physician's device).
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