Intelligent Emotion and Sensory Remote Prioritisation for Patients with Multiple Chronic Diseases

Author:

Alamoodi A. H.1ORCID,Albahri O. S.2ORCID,Zaidan A. A.3,Alsattar H. A.4,Zaidan B. B.5,Albahri A. S.6ORCID,Ismail Amelia Ritahani7,Kou Gang8ORCID,Alzubaidi Laith910ORCID,Talal Mohammed11

Affiliation:

1. Faculty of Computing and Meta-Technology (FKMT), Universiti Pendidikan Sultan Idris (UPSI), Tanjong Malim 35900, Perak, Malaysia

2. Computer Techniques Engineering Department, Mazaya University College, Nassiriya 12733, Thi-Qar, Iraq

3. SP Jain School of Global Management, Lidcombe, Sydney, NSW 2141, Australia

4. Department of Business Administration, College of Administrative Science, The University of Mashreq, Baghdad 10021, Iraq

5. Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan

6. Iraqi Commission for Computers and Informatics (ICCI), Baghdad 10022, Iraq

7. Department of Computer Science, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, Kuala Lumpur 53100, Malaysia

8. School of Business Administration, Faculty of Business Administration, Southwestern University of Finance and Economics, No. 555, Liutai Road, Wenjiang District, Chengdu 611130, China

9. School of Mechanical, Medical, and Process Engineering, Queensland University of Technology, Brisbane, QLD 4000, Australia

10. ARC Industrial Transformation Training Centre—Joint Biomechanics, Queensland University of Technology, Brisbane, QLD 4000, Australia

11. Department of Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia (UTHM), Batu Pahat 86400, Malaysia

Abstract

An intelligent remote prioritization for patients with high-risk multiple chronic diseases is proposed in this research, based on emotion and sensory measurements and multi-criteria decision making. The methodology comprises two phases: (1) a case study is discussed through the adoption of a multi-criteria decision matrix for high-risk level patients; (2) the technique for reorganizing opinion order to interval levels (TROOIL) is modified by combining it with an extended fuzzy-weighted zero-inconsistency (FWZIC) method over fractional orthotriple fuzzy sets to address objective weighting issues associated with the original TROOIL. In the first hierarchy level, chronic heart disease is identified as the most important criterion, followed by emotion-based criteria in the second. The third hierarchy level shows that Peaks is identified as the most important sensor-based criterion and chest pain as the most important emotion criterion. Low blood pressure disease is identified as the most important criterion for patient prioritization, with the most severe cases being prioritized. The results are evaluated using systematic ranking and sensitivity analysis.

Funder

Australian Research Council Industrial Transformation Training Centre

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

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