title: Predicting 5-year survival of colorectal carcinoma patients using data mining methods.
abstract: We compared the accuracy of 3 data-mining models, neural-network, decision-tree, and logistic-regression, in predicting the 5-year survival of patients with colorectal cancer. The database consisted of patient demographics, pathologic features, and levels of expression of 2 biomarkers (p53 and Bcl-2). All 3 methods demonstrated acceptable accuracy, from 64% to 70%. The neural-network model had the best specificity (80%) and accuracy (70%) but lowest sensitivity (59%). Both logistic-regression and decision-models demonstrated comparable sensitivity (72%).
authors.affiliation: Department of Pathology,University of Alabama, Birmingham, AL, USA.
authors.forename: David
authors.initials: D
authors.lastname: Chhieng
authors.forename: Michael
authors.initials: M
authors.lastname: Hardin
authors.forename: Billie
authors.initials: B
authors.lastname: Anderson
authors.forename: Upender
authors.initials: U
authors.lastname: Manne
mesh_terms: D015179:Colorectal Neoplasms / Q000401:mortality*; D003663:Decision Trees; D006801:Humans; D016247:Information Storage and Retrieval; D016015:Logistic Models; D016571:Neural Networks, Computer; D011379:Prognosis