Automated algorithms combining structure and function outperform general ophthalmologists in diagnosing glaucoma
2018
Purpose
To test the ability of machine learning classifiers (MLCs) using optical coherence tomography (OCT) and standard automated perimetry (SAP) parameters to discriminate between healthy and glaucomatous individuals, and to compare it to the diagnostic ability of the combined structure-function index (CSFI), general ophthalmologists and glaucoma specialists.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
49
References
14
Citations
NaN
KQI