Clinical Scorecard: AI in Practice: Can AI Make the Future of CLs Better?

At a Glance

Key Highlights

• AI enhances contact lens fitting efficiency by recommending optimal lens designs based on patient-specific ocular measurements.
• AI assists in selecting multifocal lenses by analyzing pupil dynamics and eye shape to improve visual outcomes.
• AI-driven analysis of large patient datasets enables matching of contact lens materials and solutions to individual ocular health needs.

Guideline-Based Recommendations

Diagnosis

• Utilize AI to analyze keratometry, eye size, sagittal depth, and pupil dynamics for precise contact lens fitting.

Management

• Incorporate AI recommendations to select off-the-rack or custom contact lenses tailored to patient eye shape and optics.
• Use AI insights to match patients with appropriate contact lens materials and care solutions based on ocular health parameters.

Monitoring & Follow-up

• Leverage AI to monitor patient responses to different lens materials and designs through objective ocular data analysis.

Risks

• Recognize that AI recommendations may not be universally applicable; individual patient variability must be considered.

Patient & Prescribing Data

Patients requiring contact lenses with optimized fit, vision, and ocular health

AI can improve prescribing accuracy by integrating ocular measurements and patient-specific data to recommend the best lens type and material.

Clinical Best Practices

• Integrate AI tools with imaging and lathing systems to enhance contact lens design capabilities.
• Collect comprehensive ocular measurements including keratometry, sagittal depth, and pupil dynamics for AI analysis.
• Use AI-driven data to personalize contact lens selection and improve patient outcomes.
• Continuously update AI databases with patient responses to refine lens recommendations.

References

• AI in Contact Lens Practice Insights