IN DECEMBER 2023, Contact Lens Spectrum published its first full-length artificial intelligence (AI)-related article (clspectrum.com/issues/2023/december/the-future-of-ai-care) covering the breadth of the impact of artificial intelligence and contact lenses. Now, one year later, AI has made a positive impact on our practices in some ways, but has hampered them in others. 

One of the most surprising things about AI is how many countries and companies have been incorporating it into their platforms in the last couple of years. This may be most pronounced in the specialty contact lens arena, where laboratories are using what they have learned from practitioners about their designs to update their databases, improving the success of lens design and fitting. While I have not seen or heard that this is being done on a large scale in the U.S., hopefully the U.S.-based laboratories will similarly use database management to fine-tune their designs while protecting patient privacy. 

In brief, this might look like the following: A laboratory utilizes its current fitting algorithm to match the topography sent from the practitioner to determine what lens design will be best for the patient. When the practitioner calls back to make adjustments, the lab will add those modifications to the learning module and apply them the next time a similar topography comes through. Multiply this by hundreds of thousands of fits, and first-fit success will inevitably go up for the lab. Incorporate additional patient data into the algorithm, and AI will make modifications to enhance success. This is already happening around the world to various extents.

July 2024’s “AI in Practice” column (clspectrum.com/issues/2024/julyaugust/ai-in-practice) mentioned that we have many challenges in the dry eye space to incorporate AI. Obstacles come from a lack of uniformity in our diagnostics and treatment algorithms across technologies. Over the course of 2024, several companies have taken this challenge on and are combining AI diagnostic assessment of images taken with their machines a treatment algorithm.

One innovation is a specific dry eye electronic health record system that is driven by AI. Practitioners enter the findings from their encounters into the system and then AI assesses severity and suggests treatments. The printouts can also aid in patient education to encourage enhanced compliance. When large databases can be built using these types of AI-driven innovations, providers will have a clearer picture of the dry eye space.

While both of these innovations are moving practitioners toward a more streamlined approach, they are only two of the true benefits that AI can bring. For example, if practitioners have diagnostic information and treatment outcome data for a million patients who were all treated with intense pulsed light, they will better know what treatments work best and what outcomes to expect. However, they would need a universal database to capture all these patients’ data. The question comes up for debate: Do we really want that or are there too many privacy barriers?

The progress of innovation in the last 12 months appears to have been faster and more profound than it was in the previous year. AI is starting to impact more and more of my clinic, and I will be excited to report back in another year on the additional progress we have made. Stay tuned.