title: Screening of prostate cancer by analyzing trace elements in hair and chemometrics.
abstract: Prostate cancer is the most common non-cutaneous malignancy and second leading cause of cancer mortality in men. The principle goal of this study was explore the feasibility of applying boosting coupled with trace element analysis of hair, for accurately distinguishing prostate cancer from healthy person. A total of 113 subjects containing 55 healthy men and 58 prostate cancers were collected. Based on a special index of variable importance and a forward selection scheme, only nine elements (i.e., Zn, Cr, Mg, Ca, Al, P, Cd, Fe, and Mo) were picked out from 20 candidate elements for modeling the relationship. As a result, an ensemble classifier consisting of only eight decision stumps achieved an overall accuracy of 98.2%, a sensitivity of 100%, and a specificity of 96.4% on the independent test set while all subjects on the training set are classified correctly. It seems that integrating boosting and element analysis of hair can serve as a valuable tool of diagnosing prostate cancer in practice.
authors: Department of Chemistry and Chemical Engineering, Yibin University, Yibin, 644007, People's Republic of China. chaotan1112@163.com
authors: Chao
authors: C
authors: Tan
authors: Hui
authors: H
authors: Chen
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D016208:Databases, Factual; D003663:Decision Trees; D005240:Feasibility Studies; D006197:Hair / Q000737:chemistry*; D006801:Humans; D008297:Male; D015233:Models, Statistical; D011471:Prostatic Neoplasms / Q000175:diagnosis*; D014131:Trace Elements / Q000032:analysis*
chemical_list: D014131:Trace Elements