A multiperiod hybrid decision support model for medical diagnosis and treatment based on similarities and three‐way decision theory. Issue 3 (7th February 2019)

• Record Type: Journal Article
• Authors: Yang, Yan; Hu, Junhua; Liu, Yongmei; Chen, Xiaohong
• Other Names: Rocha Álvaro guestEditor.; Anwar Sajid guestEditor.
• Is Part Of: Expert systems. Volume 36:Issue 3(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-02-07
• Subjects: decision support model -- medical diagnosis -- similarity -- three‐way decision theory -- treatment advice; Expert systems (Computer science); 006.33
• DOI: 10.1111/exsy.12377
• Languages: English
• ISSNs: 0266-4720

Abstract

Abstract: Patients always want a precise diagnosis and appropriate treatment advice when they are diagnosed with a disease. Furthermore, the original information about certain features and symptoms appears in different forms, and the effect of time is always ignored in the process of diagnosis. To overcome these defects, this paper develops a systematic multiperiod hybrid decision support model, which combines the similarity measurement and three‐way decision theory to provide prediction and treatment advice for patients under the fuzzy environment. This multiperiod hybrid decision support model, which considers the effect of time, including transformation module, multiperiod integration module, similarity module, prediction module, and three‐way decision module, provides disease prediction and advice on treatment based on similarities and three‐way decision theory. To validate this model, we construct an illustration composed of four cases, and this ultimately shows that MPH‐SDM can effectively support patients' disease diagnoses and treatment.