Classification of the cardiotocogram data for anticipation of fetal risks using machine learning techniques

Applied Soft Computing Journal

Volumn 33, Issue , 2015, Pages 231-238

  Sahin, Hakan ^a   Subasi, Abdulhamit ^a  

^a INTERNATIONAL BURCH UNIVERSITY   (Bosnia and Herzegovina)

Author keywords

Artificial neural network; Cardiotocogram; Decision trees; k Nearest neighbor and Random Forest; Radial basis functions; Support vector machines

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLASSIFICATION (OF INFORMATION); DECISION TREES; HEART; NEAREST NEIGHBOR SEARCH; NEURAL NETWORKS; OBSTETRICS; RADIAL BASIS FUNCTION NETWORKS; SUPPORT VECTOR MACHINES;

CARDIOTOCOGRAM; CARDIOTOCOGRAPHY (CTG); CLASSIFICATION PERFORMANCE; MACHINE LEARNING METHODS; MACHINE LEARNING TECHNIQUES; RADIAL BASIS FUNCTIONS; RANDOM FORESTS; UTERINE CONTRACTION;

LEARNING SYSTEMS;

EID: 84928987803     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2015.04.038     Document Type: Article

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