Support system for decision making in the identification of risk for body dysmorphic disorder: A fuzzy model

被引:26
|
作者
Azevedo de Britoa, Maria Jose [1 ]
Nahas, Fabio Xerfan [2 ]
Siqueira Ortega, Neli Regina [3 ]
Cordas, Taki Athandssios [4 ]
Dini, Gal Moreira [2 ]
Neto, Miguel Sabino [2 ]
Ferreira, Lydia Masako [2 ]
机构
[1] Univ Fed Sao Paulo UNIFESP, Div Plast Surg, Sao Paulo, Brazil
[2] Univ Fed Sao Paulo, Dept Surg, Sao Paulo, Brazil
[3] Univ Sao Paulo Sch Med FMUSP, Ctr Fuzzy Syst Hlth, Sao Paulo, Brazil
[4] FMUSP, Dept Psychiat, Sao Paulo, Brazil
关键词
Fuzzy logic; Plastic surgery; Body dysmorphic disorders; Somatoform disorders; Psychiatry; Investigative techniques; PLASTIC SURGEONS OPERATE; PREVALENCE; LOGIC; SETS;
D O I
10.1016/j.ijmedinf.2013.04.007
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Purpose: To develop a fuzzy linguistic model to quantify the level of distress of patients seeking cosmetic surgery. Body dysmorphic disorder (BDD) is a mental condition related to body image relatively common among cosmetic surgery patients; it is difficult to diagnose and is a significant cause of morbidity and mortality. Fuzzy cognitive maps are an efficient tool based on human knowledge and experience that can handle uncertainty in identifying or grading BDD symptoms and the degree of body image dissatisfaction. Individuals who seek cosmetic procedures suffer from some degree of dissatisfaction with appearance. Methods: A fuzzy model was developed to measure distress levels in cosmetic surgery patients based on the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), diagnostic criterion B for BDD. We studied 288 patients of both sexes seeking abdominoplasty, rhinoplasty, or rhytidoplasty in a university hospital. Results: Patient distress ranged from "none" to "severe" (range=7.5-31.6; cutoff point=18; area under the ROC curve=0.923). There was a significant agreement between the fuzzy model and DSM-IV criterion B (kappa = 0.805; p<0.001). Conclusion: The fuzzy model measured distress levels with good accuracy, indicating that it can be used as a screening tool in cosmetic surgery and psychiatric practice. (C) 2013 Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:844 / 853
页数:10
相关论文
共 50 条
  • [41] Fuzzy Logic Applied for Decision Making in a Demand Management System
    Wenzel, J. A.
    Neusser, L.
    Canha, L. N.
    2013 IEEE PES CONFERENCE ON INNOVATIVE SMART GRID TECHNOLOGIES (ISGT LATIN AMERICA), 2013,
  • [42] Fuzzy model of residential energy decision-making considering behavioral economic concepts
    Spandagos, Constantine
    Ng, Tze Ling
    APPLIED ENERGY, 2018, 213 : 611 - 625
  • [43] A Consensus Model for Group Decision Making with Hesitant Fuzzy Information
    Zhang, Zhiming
    Wang, Chao
    Tian, Xuedong
    INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS, 2015, 23 (03) : 459 - 480
  • [44] A group decision making model with hybrid intuitionistic fuzzy information
    Yue, Zhongliang
    Jia, Yuying
    COMPUTERS & INDUSTRIAL ENGINEERING, 2015, 87 : 202 - 212
  • [45] Applying a drift diffusion model to test the effect of oxytocin on attentional biases in body dysmorphic disorder
    Grennan, Gillian
    Zhao, Yuchen
    Fang, Angela
    JOURNAL OF OBSESSIVE-COMPULSIVE AND RELATED DISORDERS, 2023, 39
  • [46] FUZZY LOGIC AS A DECISION-MAKING SUPPORT TOOL IN PLANNING TRANSPORT DEVELOPMENT
    Kaczorek M.
    Jacyna M.
    Archives of Transport, 2022, 61 (01) : 51 - 70
  • [47] Decision support system for nitrogen fertilization using fuzzy theory
    Papadopoulos, A.
    Kalivas, D.
    Hatzichristos, T.
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2011, 78 (02) : 130 - 139
  • [48] Fuzzy Based Decision Support Model for Health Insurance Claim
    Susanto, Sumiatie
    Utama, Ditdit Nugeraha
    INFORMATICA-AN INTERNATIONAL JOURNAL OF COMPUTING AND INFORMATICS, 2022, 46 (07): : 119 - 130
  • [49] Decision support model under the fractional orthotriple fuzzy information
    Qiyas, Muhammad
    Khan, Neelam
    Karabasevic, Darjan
    Alvi, Muhammad Luqman
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2025, 144
  • [50] A new fuzzy decision support system approach; analysis and applications
    Hifza
    Gulistan, Muhammad
    Khan, Zahid
    Al-Shamiri, Mohammed M.
    Azhar, Muhammad
    Ali, Asad
    Madasi, Joseph David
    AIMS MATHEMATICS, 2022, 7 (08): : 14785 - 14825