Packer M, et al. Predicting visual acuity outcomes in cataract surgery using machine learning. Presented at: American Society of Cataract and Refractive Surgery. May 5-8, 2023. San Diego.
Packer reports that he is the founder of Oculotix.
- The AI model uses the optics of different IOLs and previous results from similar patients to find the best candidate.
- Patients use the app to directly send subjective feedback.
SAN DIEGO — Experts say machine learning platforms can predict vision outcomes after IOL implantation and provide direct feedback from patients.
At the DOS Digital Day of the American Society for Cataract and Refractive Surgery, Mark Packer, M.D. We have provided an overview of the Oculotix AI system. The ultimate goal of this platform is to use AI to expand the adoption of premium IOLs and improve patient outcomes.
“I’m human. What happened yesterday will affect how I feel today,” Packer said. “That’s a fallacy, isn’t it? This was my experience yesterday, not the cumulative experience of his 10,000 multifocal lenses worn over the past 25 years, so it has no real validity.”
According to Packer, the AI-based solution gives surgeons a fresh start for each patient, finding the best candidates for different IOLs without human bias.
“It’s personalized medicine based on large data pools with a more objective set of inputs and inclusions,” he said.
Packer said the AI is a “helpful robot” that utilizes different IOL optics and uses machine learning based on previous results from similar patients to tell the surgeon which lens will give the best results. said it could be
The system also includes an app for patients to submit feedback, allowing doctors to capture exactly how patients feel about their results.
According to Packer, AI-based learning models can improve the surgeon’s experience, provide quantitative predictions of visual outcomes, and improve patient awareness by providing patients with personalized experiences and desired surgical outcomes. experience can be improved.