ARTIFICIAL INTELLIGENCE AND TELE-OPTOMETRY

Abstract

Artificial Intelligence (AI) and tele-optometry represent a profound change in the future of eye care. The COVID-19 pandemic has greatly accelerated this change. This chapter will discuss how telemedicine, digital image capturing and deep learning capabilities combine to overcome barriers to obtaining eye care, especially in rural and underserved communities. By using the Internet of Medical Things (IoMT) framework, the relationship between AI and the successful identification of referable eye disease, such as diabetic retinopathy and glaucoma, how the triage of patients will be established though a hierarchy of urgency and how patients can be longitudinally monitored. In examining the comprehensive nature of the tele-optometry workflow, we will show that most high-level algorithms will be dependent on image quality, network stability, and cultural relevance. Therefore, AI will be an integral part of providing additional decision support for the increasing number of patients being seen, as well as leveling the playing field for patients, but there will still be a need to develop standardized workflows and conduct further economic analysis to identify sustainability across global health systems for the full use of AI.