Hospital Selection Framework for Remote MCD Patients Based on Fuzzy Q-rung Orthopair Environment

Overview

Journal Neural Comput Appl

Date 2022 Nov 23

PMID 36415285

Authors

A H Alamoodi

O S Albahri

A A Zaidan

H A Alsattar

B B Zaidan

A S Albahri

Affiliations

Soon will be listed here.

Abstract

This research proposes a novel mobile health-based hospital selection framework for remote patients with multi-chronic diseases based on wearable body medical sensors that use the Internet of Things. The proposed framework uses two powerful multi-criteria decision-making (MCDM) methods, namely fuzzy-weighted zero-inconsistency and fuzzy decision by opinion score method for criteria weighting and hospital ranking. The development of both methods is based on a Q-rung orthopair fuzzy environment to address the uncertainty issues associated with the case study in this research. The other MCDM issues of multiple criteria, various levels of significance and data variation are also addressed. The proposed framework comprises two main phases, namely identification and development. The first phase discusses the telemedicine architecture selected, patient dataset used and decision matrix integrated. The development phase discusses criteria weighting by q-ROFWZIC and hospital ranking by q-ROFDOSM and their sub-associated processes. Weighting results by q-ROFWZIC indicate that the time of arrival criterion is the most significant across all experimental scenarios with () for ( = ), respectively. Ranking results indicate that Hospital (H-4) is the best-ranked hospital in all experimental scenarios. Both methods were evaluated based on systematic ranking and sensitivity analysis, thereby confirming the validity of the proposed framework.

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References

Alsalem M, Albahri O, Zaidan A, Al-Obaidi J, Alnoor A, Alamoodi A . Rescuing emergency cases of COVID-19 patients: An intelligent real-time MSC transfusion framework based on multicriteria decision-making methods. Appl Intell (Dordr). 2022; 52(9):9676-9700. PMC: 8741536. DOI: 10.1007/s10489-021-02813-5. View

Almahdi E, Zaidan A, Zaidan B, Alsalem M, Albahri O, Albahri A . Mobile Patient Monitoring Systems from a Benchmarking Aspect: Challenges, Open Issues and Recommended Solutions. J Med Syst. 2019; 43(7):207. DOI: 10.1007/s10916-019-1336-z. View

Alsalem M, Zaidan A, Zaidan B, Hashim M, Albahri O, Albahri A . Systematic Review of an Automated Multiclass Detection and Classification System for Acute Leukaemia in Terms of Evaluation and Benchmarking, Open Challenges, Issues and Methodological Aspects. J Med Syst. 2018; 42(11):204. DOI: 10.1007/s10916-018-1064-9. View

Albahri O, Zaidan A, Albahri A, Zaidan B, Abdulkareem K, Al-Qaysi Z . Systematic review of artificial intelligence techniques in the detection and classification of COVID-19 medical images in terms of evaluation and benchmarking: Taxonomy analysis, challenges, future solutions and methodological aspects. J Infect Public Health. 2020; 13(10):1381-1396. PMC: 7328559. DOI: 10.1016/j.jiph.2020.06.028. View

Albahri A, Hamid R, Albahri O, Zaidan A . Detection-based prioritisation: Framework of multi-laboratory characteristics for asymptomatic COVID-19 carriers based on integrated Entropy-TOPSIS methods. Artif Intell Med. 2021; 111:101983. PMC: 7647899. DOI: 10.1016/j.artmed.2020.101983. View

Albahri O, Zaidan A, Zaidan B, Hashim M, Albahri A, Alsalem M . Real-Time Remote Health-Monitoring Systems in a Medical Centre: A Review of the Provision of Healthcare Services-Based Body Sensor Information, Open Challenges and Methodological Aspects. J Med Syst. 2018; 42(9):164. DOI: 10.1007/s10916-018-1006-6. View

Alsalem M, Zaidan A, Zaidan B, Albahri O, Alamoodi A, Albahri A . Multiclass Benchmarking Framework for Automated Acute Leukaemia Detection and Classification Based on BWM and Group-VIKOR. J Med Syst. 2019; 43(7):212. DOI: 10.1007/s10916-019-1338-x. View

Albahri O, Al-Obaidi J, Zaidan A, Albahri A, Zaidan B, Salih M . Helping doctors hasten COVID-19 treatment: Towards a rescue framework for the transfusion of best convalescent plasma to the most critical patients based on biological requirements via ml and novel MCDM methods. Comput Methods Programs Biomed. 2020; 196:105617. PMC: 7305916. DOI: 10.1016/j.cmpb.2020.105617. View

Rocha A, Martins A, Freire Junior J, Kamel Boulos M, Vicente M, Feld R . Innovations in health care services: the CAALYX system. Int J Med Inform. 2011; 82(11):e307-20. DOI: 10.1016/j.ijmedinf.2011.03.003. View

10.

Alsalem M, Alamoodi A, Albahri O, Dawood K, Mohammed R, Alnoor A . Multi-criteria decision-making for coronavirus disease 2019 applications: a theoretical analysis review. Artif Intell Rev. 2022; 55(6):4979-5062. PMC: 8791811. DOI: 10.1007/s10462-021-10124-x. View

11.

Albahri O, Albahri A, Mohammed K, Zaidan A, Zaidan B, Hashim M . Systematic Review of Real-time Remote Health Monitoring System in Triage and Priority-Based Sensor Technology: Taxonomy, Open Challenges, Motivation and Recommendations. J Med Syst. 2018; 42(5):80. DOI: 10.1007/s10916-018-0943-4. View

12.

Mohammed K, Zaidan A, Zaidan B, Albahri O, Albahri A, Alsalem M . Novel technique for reorganisation of opinion order to interval levels for solving several instances representing prioritisation in patients with multiple chronic diseases. Comput Methods Programs Biomed. 2019; 185:105151. DOI: 10.1016/j.cmpb.2019.105151. View

13.

Mohammed T, Albahri A, Zaidan A, Albahri O, Al-Obaidi J, Zaidan B . Convalescent-plasma-transfusion intelligent framework for rescuing COVID-19 patients across centralised/decentralised telemedicine hospitals based on AHP-group TOPSIS and matching component. Appl Intell (Dordr). 2021; 51(5):2956-2987. PMC: 7820530. DOI: 10.1007/s10489-020-02169-2. View

14.

Almahdi E, Zaidan A, Zaidan B, Alsalem M, Albahri O, Albahri A . Mobile-Based Patient Monitoring Systems: A Prioritisation Framework Using Multi-Criteria Decision-Making Techniques. J Med Syst. 2019; 43(7):219. DOI: 10.1007/s10916-019-1339-9. View

15.

Albahri O, Zaidan A, Albahri A, Alsattar H, Mohammed R, Aickelin U . Novel dynamic fuzzy Decision-Making framework for COVID-19 vaccine dose recipients. J Adv Res. 2022; 37:147-168. PMC: 8378994. DOI: 10.1016/j.jare.2021.08.009. View

16.

Van Dyk L . A review of telehealth service implementation frameworks. Int J Environ Res Public Health. 2014; 11(2):1279-98. PMC: 3945538. DOI: 10.3390/ijerph110201279. View

17.

Kalid N, Zaidan A, Zaidan B, Salman O, Hashim M, Albahri O . Based on Real Time Remote Health Monitoring Systems: A New Approach for Prioritization "Large Scales Data" Patients with Chronic Heart Diseases Using Body Sensors and Communication Technology. J Med Syst. 2018; 42(4):69. DOI: 10.1007/s10916-018-0916-7. View

18.

Alsalem M, Mohammed R, Albahri O, Zaidan A, Alamoodi A, Dawood K . Rise of multiattribute decision-making in combating COVID-19: A systematic review of the state-of-the-art literature. Int J Intell Syst. 2024; 37(6):3514-3624. PMC: 8653072. DOI: 10.1002/int.22699. View

19.

Alamleh A, Albahri O, Zaidan A, Albahri A, Alamoodi A, Zaidan B . Federated Learning for IoMT Applications: A Standardization and Benchmarking Framework of Intrusion Detection Systems. IEEE J Biomed Health Inform. 2022; 27(2):878-887. DOI: 10.1109/JBHI.2022.3167256. View

20.

Albahri A, Zaidan A, Albahri O, Zaidan B, Alsalem M . Real-Time Fault-Tolerant mHealth System: Comprehensive Review of Healthcare Services, Opens Issues, Challenges and Methodological Aspects. J Med Syst. 2018; 42(8):137. DOI: 10.1007/s10916-018-0983-9. View