An application of methods for the probabilistic three-class classification of pregnancies of unknown location

Artificial Intelligence in Medicine

Volumn 46, Issue 2, 2009, Pages 139-154

  Van Calster, Ben ^a   Condous, George ^b   Kirk, Emma ^c   Bourne, Tom ^c,d   Timmerman, Dirk ^d   Van Huffel, Sabine ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b NEPEAN HOSPITAL   (Australia)

^c IMPERIAL COLLEGE LONDON   (United Kingdom)

^d UNIVERSITY HOSPITALS LEUVEN   (Belgium)

Author keywords

Kernel logistic regression; Least squares support vector machines; Logistic regression; Multi class classification; Pregnancy of unknown location

Indexed keywords

KERNEL LOGISTIC REGRESSION; LEAST SQUARES SUPPORT VECTOR MACHINES; LOGISTIC REGRESSION; MULTI-CLASS CLASSIFICATION; PREGNANCY OF UNKNOWN LOCATION;

BAYESIAN NETWORKS; CLASSIFIERS; COUPLINGS; CURVE FITTING; DECISION SUPPORT SYSTEMS; IMAGE RETRIEVAL; LEAST SQUARES APPROXIMATIONS; LOGISTICS; NEURAL NETWORKS; OBSTETRICS; PATTERN RECOGNITION SYSTEMS; RADIAL BASIS FUNCTION NETWORKS; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES;

ELECTRIC REACTORS;

ADULT; ARTICLE; BAYES THEOREM; CLINICAL PRACTICE; CONTROLLED STUDY; DATA ANALYSIS; DECISION SUPPORT SYSTEM; DISEASE CLASSIFICATION; ECTOPIC PREGNANCY; FEMALE; HUMAN; KERNEL METHOD; LOGISTIC REGRESSION ANALYSIS; MAJOR CLINICAL STUDY; PERCEPTRON; PREGNANCY; PREGNANCY DISORDER; PREGNANCY OF UNKNOWN LOCATION; PREGNANCY OUTCOME; PRIORITY JOURNAL;

ALGORITHMS; FEMALE; HUMANS; LEAST-SQUARES ANALYSIS; LOGISTIC MODELS; PREGNANCY; PREGNANCY, ECTOPIC; PROBABILITY; UNCERTAINTY;

EID: 67349287660     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2008.12.003     Document Type: Article

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