Machine learning in primary care: potential to improve public health

Abstract

It is estimated that missed opportunities for diagnosis occur in 1 in 20 primary care appointments. This is not only detrimental to individual patients, but also to the healthcare system as health outcomes are affected and healthcare expenditure inevitably increases. There are many potential solutions to limit the number of missed opportunities for diagnosis and management, one of which is through the use of artificial intelligence. Artificial intelligence and machine learning research and capabilities have exponentially grown in the past decades, with their applications in medicine showing great promise. As such, this review aims to discuss the possible uses of machine learning in primary care to maximise the quality of care provided.

Keywords:

• Artificial intelligence
• machine learning
• primary care
• missed diagnosis
• population health

Author contributions

Conceptualisation: JK.

Writing – original draft: JK, MH, EM, MAK.

Writing – review & editing: JK, MH, MM.

Disclosure statement

MM is the medical director for business and product development for TKB Corporation, Japan. No potential conflict of interest was reported by the author(s).