Potential responders to FOLFOX therapy for colorectal cancer by Random Forests analysis

British Journal of Cancer

Volumn 106, Issue 1, 2012, Pages 126-132

  Tsuji, S ^a   Midorikawa, Y ^a,b,c   Takahashi, T ^d   Yagi, K ^a   Takayama, T ^c   Yoshida, K ^d   Sugiyama, Y ^b   Aburatani, H ^a  

^a UNIVERSITY OF TOKYO   (Japan)

^b TEIKYO UNIVERSITY   (Japan)

^c NIHON UNIVERSITY SCHOOL OF MEDICINE   (Japan)

^d GIFU UNIVERSITY   (Japan)

Author keywords

colorectal cancer; FOLFOX therapy; machine learning algorithm; class predictor; personalised therapy

Indexed keywords

FLUOROURACIL; FOLINIC ACID; OXALIPLATIN;

ARTICLE; CANCER PATIENT; COLORECTAL CANCER; CONTINUOUS INFUSION; DIAGNOSTIC ACCURACY; DRUG RESPONSE; FEMALE; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENE IDENTIFICATION; HUMAN; MALE; OUTCOME ASSESSMENT; PREDICTIVE VALUE; PRIORITY JOURNAL; RANDOM FOREST; RNA EXTRACTION; SENSITIVITY AND SPECIFICITY;

ANTINEOPLASTIC COMBINED CHEMOTHERAPY PROTOCOLS; COLORECTAL NEOPLASMS; FLUOROURACIL; HUMANS; LEUCOVORIN; MODELS, THEORETICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; ORGANOPLATINUM COMPOUNDS; SURVIVAL ANALYSIS;

EID: 84855356469     PISSN: 00070920     EISSN: 15321827     Source Type: Journal    
DOI: 10.1038/bjc.2011.505     Document Type: Article

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