Committee member - Dr. Hadas Ben Eli - presented a poster at the recent ARVO conference

In a study conducted at Hadassah Medical Center in collaboration with the Jerusalem Multidisciplinary Academic Center, data from 557 cataract surgeries performed by ophthalmology residents (2018–2022) were analyzed.

The aim of the study was to identify factors that predict non-clinically significant improvement in visual acuity (BCVA) after surgery, using machine learning models to create a personalized prediction tool. It was found that in 23% of patients, the improvement in visual acuity was not clinically significant.

Factors found to be associated with poorer surgical outcomes included older age, single eye, and greater eye length, while poorer preoperative visual acuity and surgery in the right eye were found to have a protective effect.

Artificial intelligence-based models have highlighted the importance of initial visual acuity, patient age, resident experience, and surgery timing in determining the chances of success for cataract surgery.