Machine Learning to Analyze the Prognostic Value of Current Imaging Biomarkers in Neovascular Age-Related Macular Degeneration

Ophthalmology Retina

Volumn 2, Issue 1, 2018, Pages 24-30

  Schmidt Erfurth, Ursula ^a   Bogunovic, Hrvoje ^a   Sadeghipour, Amir ^a   Schlegl, Thomas ^a   Langs, Georg ^a   Gerendas, Bianca S ^a   Osborne, Aaron ^b   Waldstein, Sebastian M ^a  

^a MEDICAL UNIVERSITY OF VIENNA   (Austria)

^b GENENTECH INC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL MARKER; RANIBIZUMAB;

ADULT; ARTICLE; BEST CORRECTED VISUAL ACUITY; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC IMAGING; FLUORESCENCE ANGIOGRAPHY; HUMAN; IMAGE ANALYSIS; MACHINE LEARNING; MAJOR CLINICAL STUDY; POST HOC ANALYSIS; PREDICTION; PRIORITY JOURNAL; PROGNOSTIC ASSESSMENT; PROSPECTIVE STUDY; RANDOMIZED CONTROLLED TRIAL; RETINA DETACHMENT; SPECTRAL DOMAIN OPTICAL COHERENCE TOMOGRAPHY; SUBRETINAL FLUID; WET MACULAR DEGENERATION;

EID: 85070485567     PISSN: None     EISSN: 24686530     Source Type: Journal    
DOI: 10.1016/j.oret.2017.03.015     Document Type: Article

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