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Big data problems are becoming more prevalent for laboratory scientists who look to make clinical impact. A large part of this is due to increased computing power, in parallel with new technologies for high quality data generation. Both new and old techniques of artificial intelligence (AI) and machine learning (ML) can now help increase the success of translational studies in three areas: drug discovery, imaging, and genomic medicine. However, ML technologies do not come without theirdoi:10.1016/j.ebiom.2019.08.027 pmid:31466916 pmcid:PMC6796516 fatcat:zn5cdabaabfafnyom7csumj5y4