Predicting 5-year survival of colorectal carcinoma patients using data mining methods.
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%).
Chhieng
David
D
Department of Pathology,University of Alabama, Birmingham, AL, USA.
Hardin
Michael
M
Anderson
Billie
B
Manne
Upender
U
D015179:Colorectal Neoplasms / Q000401:mortality*; D003663:Decision Trees; D006801:Humans; D016247:Information Storage and Retrieval; D016015:Logistic Models; D016571:Neural Networks, Computer; D011379:Prognosis