title: Rough set based rule induction in decision making using credible classification and preference from medical application perspective.
abstract: This paper presents a new heuristic algorithm for reduct selection based on credible index in the rough set theory (RST) applications. This algorithm is efficient and effective in selecting the decision rules particularly the problem to be solved in a large scale. This algorithm is capable to derive the rules with multi-outcomes and identify the most significant features simultaneously, which is unique and useful in solving predictive medical problems. The end results of the proposed approach are a set of decision rules that illustrates the causes for solitary pulmonary nodule and results of the long term treatment.
authors.affiliation: Department of Industrial, Manufacturing and Systems Engineering, The University of Texas at El Paso, 500 West University Avenue, El Paso, TX 79968, United States. Electronic address: btseng@utep.edu.
authors.forename: Tzu-Liang Bill
authors.initials: TL
authors.lastname: Tseng
authors.affiliation: Department of Information Management, National Chi Nan University, Taiwan, #1, University Road, Pu-Li 545, Taiwan. Electronic address: cchuang@ncnu.edu.tw.
authors.forename: Chun-Che
authors.initials: CC
authors.lastname: Huang
authors.affiliation: Barbara Hardy Institute, University of South Australia, Adelaide, Australia. Electronic address: Kym.Fraser@unisa.edu.au.
authors.forename: Kym
authors.initials: K
authors.lastname: Fraser
authors.affiliation: Department of Neurosurgery, Taipei Hospital, Taiwan, Department of Information Management, Yuan-Ze University, No. 127, Su-Yuan Rd., New Taipei City, Taiwan. Electronic address: ting.ns@gmail.com.
authors.forename: Hsien-Wei
authors.initials: HW
authors.lastname: Ting
mesh_terms: D000465:Algorithms; D003657:Decision Making
keywords: Credible index; Medical prediction; Rough set theory; Rule induction