title: A hybrid fuzzy-ontology based intelligent system to determine level of severity and treatment recommendation for Benign Prostatic Hyperplasia.
abstract: This paper deals with application of fuzzy intelligent systems in diagnosing severity level and recommending appropriate therapies for patients having Benign Prostatic Hyperplasia. Such an intelligent system can have remarkable impacts on correct diagnosis of the disease and reducing risk of mortality. This system captures various factors from the patients using two modules. The first module determines severity level of the Benign Prostatic Hyperplasia and the second module, which is a decision making unit, obtains output of the first module accompanied by some external knowledge and makes an appropriate treatment decision based on its ontology model and a fuzzy type-1 system. In order to validate efficiency and accuracy of the developed system, a case study is conducted by 44 participants. Then the results are compared with the recommendations of a panel of experts on the experimental data. Then precision and accuracy of the results were investigated based on a statistical analysis.
authors.affiliation: Department of Industrial Engineering, Amirkabir University of Technology (Tehran Polytechnic), 15875-4413 Tehran, Iran.
authors.forename: Abolfazl Doostparast
authors.initials: AD
authors.lastname: Torshizi
authors.forename: Mohammad Hossein Fazel
authors.initials: MH
authors.lastname: Zarandi
authors.forename: Ghazaleh Doostparast
authors.initials: GD
authors.lastname: Torshizi
authors.forename: Kamyar
authors.initials: K
authors.lastname: Eghbali
mesh_terms: D017143:Fuzzy Logic; D006801:Humans; D008297:Male; D011470:Prostatic Hyperplasia / Q000473:pathology* / Q000628:therapy*; D012720:Severity of Illness Index
keywords: Benign Prostatic Hyperplasia (BPH); Fuzzy rule-based systems; Ontology modeling; Prostatic disorders