An integrated methodology to control the risk of cardiovascular disease in patients with hypertension and type 1 diabetes

Abstract

Today, air pollution, smoking, use of fatty acids and ready-made foods, and so on, have exacerbated heart disease. Therefore, controlling the risk of such diseases can prevent or reduce their incidence. The present study aimed at developing an integrated methodology including Markov decision processes (MDP) and genetic algorithm (GA) to control the risk of cardiovascular disease in patients with hypertension and type 1 diabetes. First, the efficiency of GA is evaluated against Grey Wolf optimization (GWO) algorithm, and then, the superiority of GA is revealed. Next, the MDP is employed to estimate the risk of cardiovascular disease. For this purpose, model inputs are first determined using a validated micro-simulation model for screening cardiovascular disease developed at Tehran University of Medical Sciences, Iran by GA. The model input factors are then defined accordingly and using these inputs, three risk estimation models are identified. The results of these models support WHO guidelines that provide medicine with a high discount to patients with high expected LYs. To develop the MDP methodology, policies should be adopted that work well despite the difference between the risk model and the actual risk. Finally, a sensitivity

An efficient clinical support system for heart disease prediction using TANFIS classifier

“…Initialize the parameters of LGM 2 ; Formulate the initial Population (R); Estimate the objective function R: f(R); b= 1; while (b ≤ T) U p d a t ex using Equation (8); LGM 2 characterizes with good exploitation capability due to the individual moth in MFO adheres its flames through helix movement with respect to Equation (7). It follows the survival of the fittest mechanism which shows that the flames with the best fitness function value will survive for a prolonged time.…”

“…The contingent risk factors associated with heart disease encloses high blood pressure, diabetes, anomalous pulse rate, and high cholesterol. 8 In recent years, the incorporation of healthcare data with IoT developed rapidly through the amalgamation of the human body and sensor. The estimation of heart disease can be carried out through cardiac echo images obtained from echocardiogram.…”

“…Heart disease is a hazardous disease that perturbs the function of the heart and incurs severe intricacies like coronary artery infection and diminished function of blood vessels. The contingent risk factors associated with heart disease encloses high blood pressure, diabetes, anomalous pulse rate, and high cholesterol 8 . In recent years, the incorporation of healthcare data with IoT developed rapidly through the amalgamation of the human body and sensor.…”