Artificial Intelligence in Medicine: A review of challenges in implementation and disparity

Abstract

Artificial Intelligence (AI) has garnered wide interest both in the field of computer science and in the eyes of the general public. AI research has proven to be exciting and has huge potential to augment and improve many fields. The question remains though, whether AI can be implemented successfully in the fields of medicine and healthcare. Medical practice is governed by clinical guidelines, protocols and standards in order to ensure positive outcomes for the patient. Various disciplines within medicine have increasingly adopted the use of technology such as databases and communication systems to enhance healthcare services. Currently, AI has limited adoptability in clinical use, possibly due to challenges in implementation and existence of disparity in communication between AI scientists and medical personnel. In this review, we explore the key challenges that AI researchers face in terms of persuading medical practitioners to utilize AI systems for clinical practice. Industry best practices such as the development of specific quality standards and enhancing interdisciplinarity could help to bridge the gap between computer scientists, medical practitioners and medical administrators.

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