New directions for medical artificial intelligence

Abstract

The past decade has seen significant advances in medical artificial intelligence (MAI), but its role in medicine and medical education remains limited. The goal for the next decade must be directed towards maximizing the utility of MAI in the clinic and classroom. Fundamental to achieving this is increasing the involvement of clinicians in MAI development. MAI developers must move from "pet projects" toward generalizable tasks meeting recognized clinical needs. Clinical researchers must be made aware of knowledge engineering, so clinical data bases can be prospectively designed to contribute directly into MAI "knowledge bases". Closer involvement of MAI scientists with clinicians is also essential to further understanding of cognitive processes in medical decision-making. Technological advances in user interfaces--including voice recognition, natural language processing, enhanced graphics and videodiscs-- must be rapidly introduced into MAI to increase physician acceptance. Development of expert systems in non-clinical areas must expand, particularly resource management, e.g. operating room or hospital admission scheduling. The establishment of MAI laboratories at major medical centers around the country, involving both clinicians and computer scientists, represents an ideal mechanism for bringing MAI into the mainstream of medical computing.