Supervised machine learning statistical models for visual outcome prediction in macular hole surgery: a single-surgeon, standardized surgery study

Supervised machine learning statistical models for visual outcome prediction in macular hole surgery: a single-surgeon, standardized surgery study

Abstract Purpose To evaluate the predictive accuracy of various machine learning (ML) statistical models in forecasting postoperative visual acuity (VA) outcomes following macular hole (MH) surgery using preoperative optical coherence tomography (OCT) parameters. Methods This retrospective study inc...

Full description

Saved in:
Bibliographic Details
Main Authors: Kanika Godani, Vishma Prabhu, Priyanka Gandhi, Ayushi Choudhary, Shubham Darade, Rupal Kathare, Prathiba Hande, Ramesh Venkatesh
Format: Article
Language:English
Published: BMC 2025-01-01
Series:International Journal of Retina and Vitreous
Subjects:
Macular hole
Outcomes
Machine learning
Statistical models
Prediction
Online Access:https://doi.org/10.1186/s40942-025-00630-3
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1186/s40942-025-00630-3

Similar Items