title: Computer-aided intelligent system for diagnosing pediatric asthma.
abstract: Asthma is a lung chronic inflammatory disorder estimated between 1.4% and 27.1% in different area of the world. Result of various studies show that asthma is usually underdiagnosed especially in developing countries, because of limitations on access to medical specialists and laboratory facilities. In this paper, we report on the development and evaluation of a novel patient-based fuzzy system that promotes the diagnosis method of asthma. The design of this application addresses five critical issues included: 1) modular representation of asthma diagnostic variables regard to patients' perception of the disease, 2) algorithmic approaches conducting inference of diagnosing based on patient's response to questions, 4) front-end mechanism for capturing data from patient, 5) output for both patient and physician regard to asthma possibility. for the system output score (0-10) the efficacy of this system calculated in the study sample included 139 asthmatic patients and 139 non-asthmatic patients (age range 6-18) reinforce the sensitivity of 88% and specificity of 100% for cut off value 0.7.
authors: Academic Center for Education, Culture and Research, Tarbiat Modares University, Tehran, Iran. M.Zolnoori@gmail.com
authors: Maryam
authors: M
authors: Zolnoori
authors: Mohammad Hossein
authors: MH
authors: Fazel Zarandi
authors: Mostafa
authors: M
authors: Moin
authors: Hassan
authors: H
authors: Heidarnezhad
authors: Anoshirvan
authors: A
authors: Kazemnejad
mesh_terms: D000293:Adolescent; D000465:Algorithms; D001249:Asthma / Q000175:diagnosis*; D015992:Body Mass Index; D002648:Child; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004777:Environment; D017143:Fuzzy Logic; D006801:Humans; D019359:Knowledge; D008954:Models, Biological; D015203:Reproducibility of Results; D012140:Respiratory Tract Diseases / Q000175:diagnosis; D018570:Risk Assessment