Optometrists Approve of Artificial Intelligence Use in Retinal Disease Diagnosis

Optometrists are expressing positive attitudes toward artificial intelligence (AI) in clinical practice, and appear to believe the technology will serve as a diagnostic tool that will increase access to healthcare, according to research published in Ophthalmic and Physiological Optics. 

Researchers conducted a survey of 133 clinicians (mean age, 42.7±13.3 years; 44.4% women) to assess attitudes towards using AI as a method of diagnosing retinal disease and determine potential barriers to its future use. Overall, clinicians had a mean 18.8±13.2 years of experience with 64.7% of practitioners working in independent practice. 

A total of 2 clinical scenarios were presented to participants. The first involved using AI to obtain a diagnosis from an optical coherence tomography (OCT) scan. The second scenario involved using AI to provide a second opinion following patient consultation.

Clinicians considered each scenario and reported their agreement with a series of questions using a 5-point Likert scale (1, strongly disagree; 5, strongly agree). 

Overall, clinicians reported positive attitudes toward using AI to aid in the diagnosis of retinal disease (4.0±0.8), particularly if such technology would increase access to healthcare (4.4±0.6). They also reported a preference for using AI as a tool for acquiring a second opinion compared with using it for the initial diagnosis (P =.01)

No associations were noted between attitudes towards AI and age, sex, work experience, practice location, or number of patients seen. The investigators say this finding deviates from that of many medical disciplines who expressed greater skepticism about the role of these devices.

“An international survey reported few physicians (20.3%) approved of AI tools taking a dominant role over humans in diagnostic decision-making. In contrast, optometrists in our survey intended to use AI even if it surpassed human clinician involvement in clinical decision-making,” the researchers report.

Study limitations include potential geographical bias.