ABSTRACT
Both enthusiastic visions suggest that artificial intelligence (AI) and machine learning (ML) are poised to transform medicine and bring in an era of cost-effective patient care. This chapter explores basic terminology and concepts and discusses AI/Ml solutions in a variety of medical specialties. Several of the algorithms and software platforms discussed below have great promise, but not all are ready for clinical implementation. Z. Liu et al. concluded that: “Artificial intelligence algorithms can exhaustively evaluate every tissue patch on a slide, achieving higher tumor-level sensitivity than, and comparable slide level performance to, pathologists. These techniques may improve the pathologist’s productivity and reduce the number of false negatives associated with morphologic detection of tumor cells.” The AI and ML initiatives discussed are supported by varying degrees of evidence. The software embedded in IDx-DR, for instance, is supported by prospective and retrospective studies.
