Selection of relevant genes in cancer diagnosis based on their prediction accuracy

Artificial Intelligence in Medicine

Volumn 40, Issue 1, 2007, Pages 29-44

  Maglietta, Rosalia ^a   D'Addabbo, Annarita ^a   Piepoli, Ada ^b   Perri, Francesco ^b   Liuni, Sabino ^c   Pesole, Graziano ^c,d   Ancona, Nicola ^a  

^a INSTITUTE OF INTELLIGENT SYSTEMS FOR AUTOMATION   (Italy)

^b CASA SOLLIEVO DELLA SOFFERENZA HOSPITAL   (Italy)

^c CNR   (Italy)

^d UNIVERSITY OF BARI   (Italy)

Author keywords

Cancer diagnosis; Classification; DNA microarray; Gene selection; Supervised learning

Indexed keywords

COMPUTER SIMULATION; DIAGNOSIS; DNA; PATHOLOGY; SUPERVISED LEARNING; TUMORS;

CANCER DIAGNOSIS; DNA MICROARRAY; GENE SELECTION;

GENES;

ARTICLE; CANCER DIAGNOSIS; CELL CYCLE; CELL PROLIFERATION; COLON CANCER; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DNA MICROARRAY; GENE EXPRESSION; GENE OVEREXPRESSION; GENETIC ANALYSIS; HISTOPATHOLOGY; HUMAN; NUCLEOTIDE SEQUENCE; PHENOTYPE; PRIORITY JOURNAL; UNINDEXED SEQUENCE;

COLONIC NEOPLASMS; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, NEOPLASTIC; GENETIC SCREENING; HUMANS; MODELS, GENETIC; MODELS, STATISTICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PREDICTIVE VALUE OF TESTS; PROGNOSIS; TUMOR MARKERS, BIOLOGICAL;

EID: 34247535444     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2006.06.002     Document Type: Article

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