Fuzzy Inference Model for Type 2 Diabetes Management: a Tool for Regimen Alterations
نویسندگان
چکیده
This paper aims to demonstrate the utility of fuzzy set theory in the design process of a diabetes management system that enables patients to make short term alterations (particularly lifestyle) to their overall regimen as required. The model is a Mamdani Fuzzy Inference System (FIS) configured through domain specific information from experts and recognised diabetes management algorithms. The FIS takes a multi-input multi-output (MIMO) design approach with seven inputs variables (age, gender, weight, height, blood glucose (BG), exercise and diet) and three outputs (glycatedhaemoglobin (A1c), exercise and diet level assessments). Goodness of fit test was conducted based on Mean Square Error (MSE), Normalised Mean Square Error (NMSE) and Normalised Root Mean Square Error (NRMSE) between observed/advised and predicted output values. Overall MSE of 0.0899 shows good fit. For each of the output pairs (A1c, exercise and diet), NRMSE (0.7387, 0.7881 and 0.3716) and NMSE (0.9317, 0.9551 and 0.6051) shows good fit for A1c and exercise, but poor fit for diet. Intelligent models of this sort can help simplify management information for diabetes patients, reduce routine workload for clinicians and allow them to focus more on critical issues. Fully developed, this system can be used to build a database of diabetes management cases that includes daily life event information, ultimately leading to automated care for patients through technology.
منابع مشابه
CO-Active Neuro- Fuzzy Inference System Application in Supply Chain Sustainability Assessment Based on Economic, Social, Environmental, and Governance Pillars
The main aim of this study is proposing an assessment model for evaluating the supply chain sustainability across the automotive sector. In this study, through reviewing the sustainability indicators in the economic, social, environmental, and governance pillars, the fuzzy Delphi is applied. Then, survey method is used to implement the model designed in CANFIS to evaluate the sustainability ind...
متن کاملA Prioritization Model for HSE Risk Assessment Using Combined Failure Mode, Effect Analysis, and Fuzzy Inference System: A Case Study in Iranian Construction Industry
The unavailability of sufficient data and uncertainty in modeling, some techniques, and decision-making processes play a significant role in many engineering and management problems. Attain to sure solutions for a problem under accurate consideration is essential. In this paper, an application of fuzzy inference system for modeling the indeterminacy involved in the problem of HSE risk assessm...
متن کاملA Model for Evaluating Knowledge Sharing Using Fuzzy Inference System (Case Study: Tehran Municipality ICT Organization)
The present paper aimed at developing an approach based on Fuzzy Inference System (FIS) for measuring of knowledge sharing in the organization. In recent years there has been increasing interest in the knowledge sharing by experts and managers in the world, according to increasing importance of knowledge as the key source of competitive advantage, organizations have made serious effort to find ...
متن کاملNew Approach for Customer Clustering by Integrating the LRFM Model and Fuzzy Inference System
This study aimed at providing a systematic method to analyze the characteristics of customers’ purchasing behavior in order to improve the performance of customer relationship management system. For this purpose, the improved model of LRFM (including Length, Recency, Frequency, and Monetary indices) was utilized which is now a more common model than the basic RFM model apt for analyzing the cus...
متن کاملRisk Analysis of Operating Room Using the Fuzzy Bayesian Network Model
To enhance Patient’s safety, we need effective methods for risk management. This work aims to propose an integrated approach to risk management for a hospital system. To improve patient’s safety, we should develop flexible methods where different aspects of risk and type of information are taken into consideration. This paper proposes a fuzzy Bayesian network to model and analyze risk in the op...
متن کامل