Predicting macular hole surgery outcomes: Integrating preoperative OCT features with supervised machine learning statistical models
ML-based statistical models can be used to predict MH status after surgery. The RF model was the most accurate ML model, and the MHA index was the best predictor of postoperative hole closure after surgery based on preoperative OCT parameters. These predictions may help with future surgical planning for MH patients.
Authors
- Kanika Godani
- Ayushi Choudhary (ORCID: https://orcid.org/0000-0002-1317-0602)
- Rupal Kathare
- Gaurang Sehgal
- Ramesh Venkatesh (ORCID: https://orcid.org/0000-0002-4479-9390)
- Jay Kumar Chhablani (ORCID: https://orcid.org/0000-0003-1772-3558)
- Priyanka Gandhi (ORCID: https://orcid.org/0000-0002-9641-2450)
- Vishma Prabhu
- Prathiba Hande
- Shubham Darade
Institutions
- University of Pittsburgh (US)
- Narayana Nethralaya (IN)
Publication Details
- Journal
- Indian Journal of Ophthalmology
- Published
- 2024-12-24
- DOI
- https://doi.org/10.4103/ijo.ijo_1895_24
- Citations
- 1
- Primary Topic
- Retinal and Macular Surgery
- Type
- article
- Field-Weighted Citation Impact
- 0.40