The Impact of COVID-19 on Missed Ophthalmology Clinic Visits.

Purpose: To measure the COVID-19 pandemic impact on missed ophthalmology clinic visits and the influence of patient and eye disease characteristics on likelihood of missing clinic visits before and during the pandemic.

Patients And Methods: A retrospective observational study analyzing eye clinic patients at a large tertiary care academic institution. We identified patients scheduled for eye care during pre-COVID-19 (January 1-February 29, 2020) and early COVID-19 (March 16-May 31, 2020) time periods.

Artificial intelligence in global ophthalmology: using machine learning to improve cataract surgery outcomes at Ethiopian outreaches.

Differences between target and implanted intraocular lens (IOL) power in Ethiopian cataract outreach campaigns were evaluated, and machine learning (ML) was applied to optimize the IOL inventory and minimize avoidable refractive error. Patients from Ethiopian cataract campaigns with available target and implanted IOL records were identified, and the diopter difference between the two was measured. Gradient descent (an ML algorithm) was used to generate an optimal IOL inventory, and we measured the models performance across varying surplus levels.

False News of a Cannabis Cancer Cure.

Background There is increasing concern among healthcare communities about the misinformation online about using cannabis to cure cancer. We have characterized this online interest in using cannabis as a cancer treatment and the propagation of this information on social media. Materials & methods We compared search activity over time for cannabis and cancer versus standard cancer therapies using Google Trends' relative search volume (RSV) tool and determined the impact of cannabis legalization.