AIMC Topic: Cataract Extraction

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Factors influencing the estimation of phacoemulsification procedure time in cataract surgery: Analysis using neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Realistic and accurate estimation of the surgery duration is one of the key factors influencing the optimization of hospital work and, consequently, the planning and management of the budget. In the present study, the author...

PhacoTrainer: Automatic Artificial Intelligence-Generated Performance Ratings for Cataract Surgery.

Translational vision science & technology
PURPOSE: To investigate whether cataract surgical skill performance metrics automatically generated by artificial intelligence (AI) models can differentiate between trainee and faculty surgeons and the correlation between AI metrics and expert-rated ...

Beyond PhacoTrainer: Deep Learning for Enhanced Trabecular Meshwork Detection in MIGS Videos.

Translational vision science & technology
PURPOSE: The purpose of this study was to develop deep learning models for surgical video analysis, capable of identifying minimally invasive glaucoma surgery (MIGS) and locating the trabecular meshwork (TM).

Artificial Intelligence in Cataract Surgery: A Systematic Review.

Translational vision science & technology
PURPOSE: The purpose of this study was to assess the current use and reliability of artificial intelligence (AI)-based algorithms for analyzing cataract surgery videos.

PhacoTrainer: Deep Learning for Cataract Surgical Videos to Track Surgical Tools.

Translational vision science & technology
PURPOSE: The purpose of this study was to build a deep-learning model that automatically analyzes cataract surgical videos for the locations of surgical landmarks, and to derive skill-related motion metrics.

PhacoTrainer: A Multicenter Study of Deep Learning for Activity Recognition in Cataract Surgical Videos.

Translational vision science & technology
PURPOSE: To build and evaluate deep learning models for recognizing cataract surgical steps from whole-length surgical videos with minimal preprocessing, including identification of routine and complex steps.