Ovarian cancer diagnosis using a hybrid intelligent system with simple yet convincing rules

Applied Soft Computing Journal

Volumn 20, Issue , 2014, Pages 25-39

  Wang, Di ^a   Quek, Chai ^a   See Ng, Geok ^b  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b SINGAPORE UNIVERSITY OF TECHNOLOGY AND DESIGN   (Singapore)

Author keywords

Decision support system; Feature selection; Hybrid intelligent system; Interpretability; Ovarian cancer diagnosis

Indexed keywords

CELLS; DECISION SUPPORT SYSTEMS; DIAGNOSIS; FEATURE EXTRACTION; INTELLIGENT SYSTEMS;

ATTRIBUTE REDUCTION; CONTROL PARAMETERS; HUMAN INTERVENTION; HYBRID INTELLIGENT SYSTEM; INTERPRETABILITY; MEDICAL DATA SETS; NEURAL FUZZY INFERENCE SYSTEMS; OVARIAN CANCER DIAGNOSIS;

DISEASES;

EID: 84901623406     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2013.12.018     Document Type: Article

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