MRMR optimized classification for automatic glaucoma diagnosis

Min-Redundancy Max-Relevance (mRMR) is a feature selection methodology based on information theory. We explore the mRMR principle for automatic glaucoma diagnosis. Optimal candidate feature sets are acquired from a composition of clinical screening data and retinal fundus image data. An mRMR optimiz...

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Hauptverfasser:	Zhuo Zhang, Chee Keong Kwoh, Jiang Liu, Fengshou Yin, Wirawan, A., Cheung, C., Baskaran, M., Tin Aung, Tien Yin Wong
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Algorithms Area Under Curve Artificial Intelligence Automatic Data Processing Biomedical optical imaging Databases, Factual Decision Support Systems, Clinical Diagnosis, Computer-Assisted - methods Diagnostic Imaging - methods Feature extraction Glaucoma - diagnosis Glaucoma - pathology Humans Models, Statistical Ophthalmoscopy - methods Optical fibers Optical imaging Reproducibility of Results Retina
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