Artificial intelligence (AI) allows computers to imitate human cognitive functions, such as deep learning, problem solving, and creativity. In recent years, AI has prompted a series of innovations in the medical field. Clinical applications of AI are most advanced in image- and signal-intensive disciplines, including radiology, dermatology, and critical care. It's in these contexts that the performance of AI algorithms for many tasks now meets or exceeds that of individual clinicians.
Primary care supports the health of all members of society and is primed to realize the benefits of AI on a broad scale. Primary care electronic health records contain longitudinal data that span diseases, care settings, socioeconomic circumstances, and life experiences. Applications of AI to these and other linked data (eg, from wearable devices) can enable proactive care and clinical decision support in primary care.
Examples of primary care–targeted AI applicationsunder development in the public sector include automating checks on clinical decisions in real time against chronic disease guidelines, detecting signs of dementia, and predicting outcomes such as nonelective hospitalizations. Despite optimism for the use of AI in primary care, there has been no comprehensive review of the contribution made by AI so far, and there is little guidance on how it should proceed.
