Current and future directions for the use of handheld fundus cameras in telehealth.

Abstract

Introduction: A shortage of trained retinal specialists has created a growing need for a telehealth retinal screening alternative. Recent developments in handheld fundus cameras, enhanced by artificial intelligence (AI) and machine learning (ML) methods, have created a promising avenue to satisfy the unmet need for efficient retinal disease screening. This paper discusses the state of current handheld fundus cameras as well as promising future directions.

Areas covered: Commercially available handheld fundus cameras and the current and future developments in telehealth retinal screenings using these cameras are discussed. Relevant literature encompassing handheld fundus cameras, diagnostic accuracy, and AI in grading were included. Commercial handheld fundus cameras were targeted in the literature and from their company websites. Additional information was obtained through dialogs with company representatives.

Expert opinion: Handheld fundus cameras utilized for telehealth retinal screening have shown success in multiple small-scale studies. To make their usage more widespread, multiple technical, technological, and methodical barriers must be addressed. This can be accomplished by improving the technology, utilizing AI, and developing telehealth guidelines.