Health Symptom Checking System for Elderly People Using Fuzzy Analytic Hierarchy Process

Abstract

The ever-escalating rise in numbers of the aging population has preempted a revolutionary change in the healthcare sector and serves as a major counterpoint to modern life in the 21st century. Increasing demand being placed on the health sector is almost certainly an inevitable process. However, providing appropriate healthcare services is requisite for senior citizens who suffer from various health issues and conditions. To minimize these health risks, we derived an intuitive technique for determining the incongruity of health symptoms by using a symptom checker, which is embedded into a versatile mobile app named Help-to-You (H2U). The designed app helps the users and carers to determine and identify conceivable reasons for elderly ailments and to assist users in deciding when to counsel a health practitioner. The intention of this empirical study was to further analyze and foresee certain variations of infections based on the symptoms accounted for by the patient. The recommended solution consolidated conceptual design with multi-criteria decision analysis (MCDA) technique and an analytic hierarchy process (AHP) with fuzzy weights to deal with the uncertainty of imprecision and ambiguity resulting from various disease factors. Experimental results verified the effectiveness of the proposed model, subsequently providing a variety of life assistance services.

A Fuzzy-Ontology Based Diabetes Monitoring System Using Internet of Things

“…For instance, Mumtaj et al [10] proposed an IoT-based system combining ANN and fuzzy logic and aims to ensure the monitoring of elderly and supports caregivers to diagnose diseases by sending alerts in case of any abnormalities. Huang et al [6] introduced predictive symptom checker system based fuzzy logic that helps the elderly to decisively determine the most appropriate illness and any health-related threats. Another system presented in [11] aims to evaluate the likelihood of developing heart diseases in patients.…”

Risk Assessment and Mitigation Model for Overseas Steel-Plant Project Investment with Analytic Hierarchy Process—Fuzzy Inference System

“…One of the more frequently used modelling tools has been fuzzy-logic-based methods due to their appropriateness to address uncertainty and subjectivity in decision-making processes [24]. FIS and/or fuzzy-AHP analysis have been used to rank water quality indicators [24], aid in environmental management decision-making [25,26], assess the quality and sustainability of supply chains [27][28][29][30], evaluate manufacturing processes [31], manage investment portfolios [32], provide the appropriate healthcare services for senior citizens [33], optimize the liquefied natural gas importation in Korea [34], optimize robot path selections of mobile robots [35], optimize joint distribution alliance partnerships [36], assess emerging three-dimensional integrated circuit technologies [37], assess potassium saturation of calcareous soils [38], evaluate the land suitability for a multitude of purposes [39], evaluate barriers of corporate social responsibility [40], and aid a multitude of other decision-making processes. Concerning the risks of technology transfer, fuzzy analysis was used to aid technology-based decisions for information technology organizations competing in global markets [41] and in transferring biotechnology [42].…”

Israeli Medical Experts’ Knowledge, Attitudes, and Preferences in Allocating Donor Organs for Transplantation

“…For liver allocation, a rule-based decision-making system was proposed by Cruz-Ramirez in 2013 [ 15 ]. In parallel, linear regression of score weights [ 16 ], fuzzy lung allocation system (FLAS) [ 17 ], Data Envelopment Analysis (DEA) [ 18 ], Delphi method, Analytic Hierarchy Process (AHP) [ 19 , 20 , 21 ], and Mamdani Style Fuzzy Inference System (MSFIS) [ 22 ] were developed and practiced for allocating organ in different regions at different time. Altogether, AHP and Delphi have been extensively used for developing the organ allocation system [ 19 , 20 , 21 ].…”