Objective:

To explore the integration of AI into clinical practice for eyecare providers, emphasizing its practical benefits and implications.

Key Findings:

• AI can analyze clinical data and predict outcomes based on large datasets, potentially improving patient care.
• AI may assist in diagnosing conditions and suggesting treatments when provided with specific clinical scenarios, but clinician verification is essential.
• Clinicians must verify AI suggestions against their clinical expertise and available evidence to ensure patient safety.

Interpretation:

AI has the potential to enhance clinical decision-making by providing alternative perspectives and research-based outcomes, but it should not replace clinical judgment; clinician oversight is crucial.

Limitations:

• Privacy concerns and lack of electronic health record interoperability may hinder AI's full potential, impacting data access and analysis.
• AI can incorporate false information from the internet, necessitating careful validation by clinicians to avoid misdiagnosis.

Conclusion:

While AI can serve as a valuable tool in clinical practice, it is essential for eyecare practitioners to maintain their role as the primary decision-makers in patient care, ensuring that AI complements rather than replaces their expertise.