Machine learning and big data: Implications for disease modeling and therapeutic discovery in psychiatry

作者：

Highlights：

•

摘要

IntroductionMachine learning capability holds promise to inform disease models, the discovery and development of novel disease modifying therapeutics and prevention strategies in psychiatry. Herein, we provide an introduction on how machine learning/Artificial Intelligence (AI) may instantiate such capabilities, as well as provide rationale for its application to psychiatry in both research and clinical ecosystems.

论文关键词：Big data,Machine learning,Precision medicine,AI,Mental health,Mental disease,Psychiatry,Data mining,RDoC,Research domain criteria,DSM-5. Schizophrenia,ADHD,Alzheimer,Depression,fMRI,MRI,Algorithms,IBM Watson,Neuro networking,Random forests,Decision trees,Support vector machines

论文评审过程：Received 11 April 2017, Revised 4 March 2019, Accepted 8 August 2019, Available online 9 August 2019, Version of Record 21 August 2019.

论文官网地址：https://doi.org/10.1016/j.artmed.2019.101704