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Bimodal fuzzy analytic hierarchy process (BFAHP) for coronary heart disease risk assessment
1Soft Computing Laboratory, Faculty of Electrical and Computer Engineering, Urmia University, Urmia, Iran.
Insights
A new Bimodal Fuzzy Analytic Hierarchy Process (BFAHP) improves coronary heart disease (CHD) risk assessment by incorporating fuzzy validity and probability, achieving over 85% prediction accuracy. This method enhances confidence in results, especially with incomplete medical data.
Area of Science:
- Medical Decision Making
- Health Informatics
- Biostatistics
Background:
- Coronary heart disease (CHD) risk assessment is crucial but complex due to stochastic and uncertain variables.
- Traditional methods struggle with the inherent uncertainty in medical decision-making.
- Fuzzy Analytic Hierarchy Process (FAHP) is a popular methodology for handling uncertainty in multi-criteria decision-making (MCDM).
Purpose of the Study:
- To introduce a novel Bimodal Fuzzy Analytic Hierarchy Process (BFAHP) for enhanced CHD risk assessment.
- To augment fuzzy numbers with probability and validity to better manage uncertainty in risk assessment.
- To improve the accuracy and confidence of CHD risk prediction, particularly with incomplete information.
Main Methods:
- Developed BFAHP by incorporating fuzzy validity (aggregated expert knowledge) and fuzzy probability (Bayesian formulation).
- Constructed a reciprocal comparison matrix using fuzzy validities and probabilities.
- Applied BFAHP to a real dataset of 152 patients for CHD risk assessment, evaluating prediction accuracy.
Main Results:
- The BFAHP approach achieved a high accuracy rate exceeding 85% for correct CHD risk prediction.
- Incorporating fuzzy validity increased confidence in the assessment results, proving clinically useful with incomplete data.
- Identified diastolic blood pressure in men and high-density lipoprotein in women as key risk factors for CHD.
Conclusions:
- BFAHP offers a robust and accurate method for medical risk assessment, outperforming existing approaches.
- The inclusion of fuzzy validity significantly enhances the reliability of risk predictions in uncertain medical scenarios.
- The findings provide valuable insights into specific risk factors for CHD, aiding targeted prevention strategies.
Abstract:
Rooted deeply in medical multiple criteria decision-making (MCDM), risk assessment is very important especially when applied to the risk of being affected by deadly diseases such as coronary heart disease (CHD). CHD risk assessment is a stochastic, uncertain, and highly dynamic process influenced by various known and unknown variables. In recent years, there has been a great interest in fuzzy analytic hierarchy process (FAHP), a popular methodology for dealing with uncertainty in MCDM. This paper proposes a new FAHP, bimodal fuzzy analytic hierarchy process (BFAHP) that augments two aspects of knowledge, probability and validity, to fuzzy numbers to better deal with uncertainty. In BFAHP, fuzzy validity is computed by aggregating the validities of relevant risk factors based on expert knowledge and collective intelligence. By considering both soft and statistical data, we compute the fuzzy probability of risk factors using the Bayesian formulation. In BFAHP approach, these fuzzy validities and fuzzy probabilities are used to construct a reciprocal comparison matrix. We then aggregate fuzzy probabilities and fuzzy validities in a pairwise manner for each risk factor and each alternative. BFAHP decides about being affected and not being affected by ranking of high and low risks. For evaluation, the proposed approach is applied to the risk of being affected by CHD using a real dataset of 152 patients of Iranian hospitals. Simulation results confirm that adding validity in a fuzzy manner can accrue more confidence of results and clinically useful especially in the face of incomplete information when compared with actual results. Applying the proposed BFAHP on CHD risk assessment of the dataset, it yields high accuracy rate above 85% for correct prediction. In addition, this paper recognizes that the risk factors of diastolic blood pressure in men and high-density lipoprotein in women are more important in CHD than other risk factors.
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