The acceptance of ophthalmic artificial intelligence for eye diseases: a literature review and qualitative analysis

Thorough investigations of end-users' awareness, acceptance, and concerns about ophthalmic artificial intelligence (AI) are essential to ensure its successful implementation. We conducted a literature review on the acceptance of ophthalmic AI to provide an overall insight and qualitatively analysed the quality of eligible studies using a psychological model. We identified sixteen studies and evaluated these studies based on four primary factors (i.e., performance expectancy, effort expectancy, social influence, and facilitating conditions) and four regulating factors (i.e., gender, age, experiences, and voluntariness of use) of the psychological model. We found that most of the eligible studies only emphasized performance expectancy and effort expectancy, and in-depth discussions on the effects of social influence, facilitating conditions, and relevant regulating factors were relatively inadequate. The overall acceptance of ophthalmic AI among specific groups, such as patients with different eye diseases, experts in ophthalmology, professionals in other fields, and the general population, is high. Nevertheless, more well-designed qualitative studies with clear definitions of acceptance and using proper psychological models with larger sample sizes involving other representative and multidisciplinary stakeholders worldwide are still warranted. In addition, because of the multifarious concerns of AI, such as the economic burden, patient privacy, model safety, model trustworthiness, public awareness, and proper regulations over accountability issues, it is imperative to focus on evidence-based medicine, conduct high-quality randomized controlled trials, and promote patient education. Comprehensive clinician training, privacy-preserving technologies, and the issue of cost-effectiveness are also indispensable to address the above concerns and further propel the overall acceptance of ophthalmic AI.