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DRUG INDICATION AND RESPONSE PREDICTION SYSTEMS AND METHOD USING AI DEEP LEARNING BASED ON CONVERGENCE OF DIFFERENT CATEGORY DATA

机译:基于不同类别数据融合的人工智能深度学习的药物指示和响应预测系统及方法

摘要

A system of predicting drug indications and drug response using an artificial intelligence (AI) deep learning model based on convergence of different types of information, the system including: a learning module configured to learn the response correlation between structure information on a drug and genetic information on a genome from collected learning information by deep machine learning; a prediction module configured to receive analysis information and output the result of prediction of the response of the genome to the drug from the analysis information; and a storage module configured to store a response prediction algorithm learned by the learning module. The learning information is drug response information obtained from clinical drug response information on target proteins, cell lines or living bodies.
机译:一种基于不同类型信息的融合,使用人工智能(AI)深度学习模型预测药物适应症和药物反应的系统,该系统包括:学习模块,配置为学习药物结构信息和遗传信息之间的反应相关性通过深度机器学习从收集的学习信息中提取基因组;预测模块,用于接收分析信息,并从分析信息中输出基因组对药物反应的预测结果;存储模块,用于存储所述学习模块学习到的响应预测算法。学习信息是从关于靶蛋白,细胞系或活体的临床药物反应信息获得的药物反应信息。

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