AI platform can be a ‘helpful robot’ for cataract surgery
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Key takeaways:
- The AI model uses optics from different IOLs as well as previous outcomes from similar patients to find the best candidates.
- Patients use an app to directly submit subjective feedback.
SAN DIEGO — A machine learning platform can provide predictions for vision outcomes after IOL implantation, as well as direct patient feedback, according to an expert.
At DOS Digital Day at the American Society of Cataract and Refractive Surgery meeting, Mark Packer, MD, gave an overview of the Oculotix AI system. The ultimate goal of the platform, he said, is to use AI to expand premium IOL adoption and improve patient outcomes.
Image: Adobe Stock
“I’m human, and what happened yesterday is going to impact how I feel today,” Packer said. “That’s a fallacy, right? That has no real validity because it’s just my experience yesterday, not my pooled experience over the 10,000 multifocal lenses I’ve put in over the last 25 years.”
Packer said AI-based solutions offer surgeons a fresh start with each patient and can find the best candidates for various IOLs without biases that come with being a human.
“It’s personalized medicine based on a large pool of data with a more objective set of inputs and inclusions,” he said.
Packer said AI can be a “helpful robot” that takes the optics of the different IOLs and uses machine learning based on previous outcomes from similar patients to tell the surgeon what lens will produce the best results.
The system also includes an app for patients to submit feedback, allowing physicians to glean exactly how patients feel about their outcomes.
Packer said the AI-based learning model can improve the experience for surgeons by providing quantitative prediction of vision outcomes and for patients by giving them a personalized experience and the surgical outcomes they desire.
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Packer M, et al. Predicting vision outcomes in cataract surgery with machine learning. Presented at: American Society of Cataract and Refractive Surgery meeting; May 5-8, 2023; San Diego.
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