Soft computing decision making system to analyze the risk factors of T2DM

Felix, A.; Kumar, Rajesh; Parthiban, A.

doi:10.1063/1.5112271

“…q PROMETHEE: preference ranking organization method for enrichment of evaluations. Combined WPM method with machine learning to select the best model N/A Forecast diabetes WPM o Malapane et al [52] Blindness, obesity, and inactivity were the risk factors with greatest impact Blood glucose, BP, blood cholesterol, obesity, blindness, physical inactivity Identification of the most important T2D risk factors in the Pima Indian database TOPSIS Felix et al [53] Propose a model for predicting diabetes among women N/A Forecast diabetes in women AHP Sankar and Jeyaraj [54] Proposed a new algorithm which removed the multicollinearity among criteria…”

Section: Objective Methods Referencementioning

confidence: 99%

Multicriteria Decision-Making in Diabetes Management and Decision Support: Systematic Review

Aldaghi,

Muzik

2024

JMIR Med Inform

4

0

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Background Diabetes mellitus prevalence is increasing among adults and children around the world. Diabetes care is complex; examining the diet, type of medication, diabetes recognition, and willingness to use self-management tools are just a few of the challenges faced by diabetes clinicians who should make decisions about them. Making the appropriate decisions will reduce the cost of treatment, decrease the mortality rate of diabetes, and improve the life quality of patients with diabetes. Effective decision-making is within the realm of multicriteria decision-making (MCDM) techniques. Objective The central objective of this study is to evaluate the effectiveness and applicability of MCDM methods and then introduce a novel categorization framework for their use in this field. Methods The literature search was focused on publications from 2003 to 2023. Finally, by applying the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method, 63 articles were selected and examined. Results The findings reveal that the use of MCDM methods in diabetes research can be categorized into 6 distinct groups: the selection of diabetes medications (19 publications), diabetes diagnosis (12 publications), meal recommendations (8 publications), diabetes management (14 publications), diabetes complication (7 publications), and estimation of diabetes prevalence (3 publications). Conclusions Our review showed a significant portion of the MCDM literature on diabetes. The research highlights the benefits of using MCDM techniques, which are practical and effective for a variety of diabetes challenges.

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“…q PROMETHEE: preference ranking organization method for enrichment of evaluations. Combined WPM method with machine learning to select the best model N/A Forecast diabetes WPM o Malapane et al [52] Blindness, obesity, and inactivity were the risk factors with greatest impact Blood glucose, BP, blood cholesterol, obesity, blindness, physical inactivity Identification of the most important T2D risk factors in the Pima Indian database TOPSIS Felix et al [53] Propose a model for predicting diabetes among women N/A Forecast diabetes in women AHP Sankar and Jeyaraj [54] Proposed a new algorithm which removed the multicollinearity among criteria…”

Section: Objective Methods Referencementioning

confidence: 99%

Multicriteria Decision-Making in Diabetes Management and Decision Support: Systematic Review (Preprint)

Aldaghi,

Muzik

2023

Preprint

0

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BACKGROUND Diabetes mellitus prevalence is increasing among adults and children around the world. Diabetes care is complex; examining the diet, type of medication, diabetes recognition, and willingness to use self-management tools are just a few of the challenges faced by diabetes clinicians who should make decisions about them. Making the appropriate decisions will reduce the cost of treatment, decrease the mortality rate of diabetes, and improve the life quality of patients with diabetes. Effective decision-making is within the realm of multicriteria decision-making (MCDM) techniques. OBJECTIVE The central objective of this study is to evaluate the effectiveness and applicability of MCDM methods and then introduce a novel categorization framework for their use in this field. METHODS The literature search was focused on publications from 2003 to 2023. Finally, by applying the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method, 63 articles were selected and examined. RESULTS The findings reveal that the use of MCDM methods in diabetes research can be categorized into 6 distinct groups: the selection of diabetes medications (19 publications), diabetes diagnosis (12 publications), meal recommendations (8 publications), diabetes management (14 publications), diabetes complication (7 publications), and estimation of diabetes prevalence (3 publications). CONCLUSIONS Our review showed a significant portion of the MCDM literature on diabetes. The research highlights the benefits of using MCDM techniques, which are practical and effective for a variety of diabetes challenges.

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