Predicting neuroendocrine tumor (carcinoid) neoplasia using gene expression profiling and supervised machine learning

Cancer

Volumn 115, Issue 8, 2009, Pages 1638-1650

  Drozdov, Ignat ^a   Kidd, Mark ^a   Nadler, Boaz ^b   Camp, Robert L ^b   Mane, Shrikant M ^a   Hauso, Oyvind ^a   Gustafsson, Bjorn I ^a,c   Modlin, Irvin M ^a  

^a YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b WEIZMANN INSTITUTE OF SCIENCE   (Israel)

^c NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Norway)

Author keywords

Algorithm; Gene; Neuroendocrine; Predict; Real time polymerase chain reaction

Indexed keywords

CHROMOGRANIN A; KI 67 ANTIGEN; MELANOMA ANTIGEN; MELANOMA ANTIGEN D2; NEUROPILIN 2; SURVIVIN; UNCLASSIFIED DRUG;

ARTICLE; CARCINOGENICITY; CARCINOID; CELL DIFFERENTIATION; CONTROLLED STUDY; ENTEROCHROMAFFIN CELL; FZD7 GENE; GENE; GENE EXPRESSION PROFILING; GENETIC TRANSCRIPTION; HORMONE SYNTHESIS; HUMAN; HUMAN CELL; KISS1 GENE; LIVER METASTASIS; MACHINE LEARNING; NAPIL1 GENE; NEUROENDOCRINE TUMOR; PRIORITY JOURNAL; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; AUTOMATIC DATA PROCESSING; CARCINOID TUMOR; ENTEROCHROMAFFIN CELLS; FROZEN SECTIONS; GENE EXPRESSION PROFILING; HUMANS; INTESTINAL NEOPLASMS; NEOPLASM METASTASIS; PREDICTIVE VALUE OF TESTS; SENSITIVITY AND SPECIFICITY; VALIDATION STUDIES AS TOPIC;

EID: 65249120253     PISSN: 0008543X     EISSN: 10970142     Source Type: Journal    
DOI: 10.1002/cncr.24180     Document Type: Article

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