Probabilistic graphical models and deep belief networks for prognosis of breast cancer

Proceedings - 2015 IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015

Volumn , Issue , 2016, Pages 727-732

  Khademi, Mahmoud ^a   Nedialkov, Nedialko S ^a  

^a MCMASTER UNIVERSITY   (Canada)

Author keywords

Breast cancer; Deep belief networks; Microarray data; Probabilistic graphical models

Indexed keywords

ARTIFICIAL INTELLIGENCE; BAYESIAN NETWORKS; CLASSIFICATION (OF INFORMATION); DIAGNOSIS; DISEASES; GRAPHIC METHODS; LEARNING ALGORITHMS; LEARNING SYSTEMS; MEDICAL APPLICATIONS; NEAREST NEIGHBOR SEARCH; SPEECH RECOGNITION; SUPPORT VECTOR MACHINES;

BREAST CANCER; DEEP BELIEF NETWORKS; MICROARRAY DATA; PROBABILISTIC GRAPHICAL MODELS; PROBABILISTIC GRAPHICAL MODELS (PGM); SMALL SAMPLE SIZE PROBLEMS; STRUCTURE LEARNING ALGORITHM; SUPPORT VECTOR MACHINE (SVMS);

BIG DATA;

EID: 84969622676     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMLA.2015.196     Document Type: Conference Paper

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