Exploration of machine learning techniques in predicting multiple sclerosis disease course

PLoS ONE

Volumn 12, Issue 4, 2017, Pages

  Zhao, Yijun ^a   Healy, Brian C ^b,c   Rotstein, Dalia ^b   Guttmann, Charles R G ^b   Bakshi, Rohit ^b   Weiner, Howard L ^b   Brodley, Carla E ^d   Chitnis, Tanuja ^b  

^a Tufts University   (United States)

^b BRIGHAM AND WOMEN S HOSPITAL   (United States)

^c MASSACHUSETTS GENERAL HOSPITAL   (United States)

^d NORTHEASTERN UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ADULT; ARTICLE; CLASSIFIER; CLINICAL EXAMINATION; CLINICAL OBSERVATION; DEMOGRAPHY; DIAGNOSTIC TEST ACCURACY STUDY; DISEASE COURSE; DISEASE EXACERBATION; EXPANDED DISABILITY STATUS SCALE; FAMILY HISTORY; FEMALE; FOLLOW UP; HUMAN; LOGISTIC REGRESSION ANALYSIS; MACHINE LEARNING; MAJOR CLINICAL STUDY; MALE; MULTIPLE SCLEROSIS; NUCLEAR MAGNETIC RESONANCE IMAGING; PREDICTION; PREDICTIVE VALUE; PROGNOSIS; RACE; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE; BRAIN; DIAGNOSTIC IMAGING; NEUROIMAGING; PATHOLOGY; STATISTICAL MODEL;

ADULT; BRAIN; DISEASE PROGRESSION; FEMALE; HUMANS; LOGISTIC MODELS; MACHINE LEARNING; MAGNETIC RESONANCE IMAGING; MALE; MULTIPLE SCLEROSIS; NEUROIMAGING; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE;

EID: 85016992939     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0174866     Document Type: Article

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