 A new model for physician assignment based on fuzzy rules extraction from climatic factorsSima Hadadian, Zahra Naji-Azimi, Nasser Motahari Farimani and Behrouz Minaei-Bidgoli International Journal of Operational Research, 2024, vol. 49, issue 2, 204-230 Abstract: The number of patients should be predicted to meet the physicians' demands in hospitals. In this study, a new multi-objective physician assignment model was designed based on the number of the patients estimated by the climatic factors. The number of patients was predicted through multiple linear regression (MLR) and fuzzy inference system (FIS). In the FIS, the feature selection was performed by the genetic-K-nearest neighbour (k-NN) algorithm. Then, fuzzy rules were extracted using fuzzy associative classification. After predicting the number of patients, the physician assignment model was designed. The case study is a paediatric hospital with four wards. The results indicated some medical fuzzy rules based on climatic factors. In addition, RMSE and MAE, as compared with MLR in all hospital wards, had a lower value in the FIS. Finally, the advantage of the assignment model could be attributed to its sensitivity to changes in the number of the patients. Keywords: multi-objective model; physician assignment; fuzzy associative classification; FAC; fuzzy inference system; FIS; genetic-K-nearest neighbour algorithm; multiple linear regression; MLR. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijores:v:49:y:2024:i:2:p:204-230 Access Statistics for this article More articles in International Journal of Operational Research from Inderscience Enterprises Ltd |
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