An Integrated Decision Support System for Hospital Management: Statistical-Based Fuzzy Cognitive Maps


DOĞU E., ALBAYRAK Y. E., Tuncay E.

JOURNAL OF MULTIPLE-VALUED LOGIC AND SOFT COMPUTING, cilt.34, ss.527-552, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 34
  • Basım Tarihi: 2020
  • Dergi Adı: JOURNAL OF MULTIPLE-VALUED LOGIC AND SOFT COMPUTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, zbMATH
  • Sayfa Sayıları: ss.527-552
  • Anahtar Kelimeler: Statistical-based fuzzy cognitive maps, chronic obstructive pulmonary disease, risk factors, length of stay predictors, medical decision making, LENGTH-OF-STAY, OBSTRUCTIVE PULMONARY-DISEASE, READMISSION, COPD, EXACERBATIONS, DIAGNOSIS, RISK, ASSOCIATION, IMPACT, CARE
  • Galatasaray Üniversitesi Adresli: Evet

Özet

Chronic Obstructive Pulmonary Disease (COPD) is one of the most common chronic respiratory diseases. COPD is a global burden that induces many decision-making problems. Medical decisions are naturally originated from personal experience of the physician and statistical analysis of previous data. Because of its structural advantages in revealing the behavior of complex systems, and in capturing human judgment by means of fuzzy information, Fuzzy Cognitive Map (FCM) and its extensions are widely used in medical decisions. In this paper, a novel approach called Statistical-Based Fuzzy Cognitive Map (SBFCM) is proposed which aggregates the power of statistical analysis with dynamical nature FCMs. The SBFCM method is developed in order to evaluate the factors that affect the length of hospital stay (LoS) of COPD patients that apply to the hospital with an acute exacerbation. Fifty factors, including LoS, are adopted as system concepts and observed under four groups. A real-case application is conducted and different scenarios are analyzed for a better understanding of the system behavior.