Evaluation of prediction errors in nine intraocular lens calculation formulas using an explainable machine learning model
The explanatory power of currently used ocular biometric variables for PEs in new-generation formulas such as BUII, Cooke K6, EVO V2.0 and Kane is low, implying that these formulas are already optimized. Therefore, the introduction of new ocular biometric variables into IOL calculation formulas could potentially reduce PEs, enhancing the accuracy of surgical outcomes.
Authors
- Hyuk Jin Choi (ORCID: https://orcid.org/0000-0001-9806-8676)
- Joo Youn Oh (ORCID: https://orcid.org/0000-0002-7899-5314)
- Richul Oh (ORCID: https://orcid.org/0000-0003-3221-5121)
- Chang Ho Yoon (ORCID: https://orcid.org/0000-0003-1356-0392)
- Mee Kum Kim (ORCID: https://orcid.org/0000-0001-7850-6894)
Institutions
- Seoul National University (KR)
- New Generation University College (ET)
- Seoul National University Hospital (KR)
Publication Details
- Journal
- BMC Ophthalmology
- Published
- 2024-12-18
- DOI
- https://doi.org/10.1186/s12886-024-03801-2
- Citations
- 2
- Primary Topic
- Intraocular Surgery and Lenses
- Type
- article
- Field-Weighted Citation Impact
- 1.08