User Awareness in AI-Based Retinal Screening Systems
Keywords:
Artificial Intelligence, Retinal Screening, User Awareness, Ophthalmology, Medical Imaging, Trust in AI etcAbstract
Artificial Intelligence (AI) is reshaping eye care by making retinal screening faster and more accurate. These systems detect conditions such as diabetic retinopathy, glaucoma, and age-related macular degeneration with high precision. However, technology alone does not guarantee success. The way patients, doctors, and institutions understand and trust AI plays a decisive role in whether these systems are widely adopted. Patients often worry about machines replacing human judgment, while clinicians may hesitate to rely on automated results without clear explanations. Institutions face challenges in balancing innovation with ethical, financial, and regulatory responsibilities. This paper highlights the importance of user awareness in bridging the gap between advanced AI tools and everyday clinical practice. It examines current barriers, including limited transparency, ethical concerns, and cultural differences, and suggests strategies such as patient education, clinician training, and clears communication of AI’s strengths and limitations. Building awareness improves trust and ensures smoother integration into healthcare systems. Raising awareness is as important as improving algorithms, because informed users are more likely to accept and benefit from AI-driven retinal screening.
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References
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