Fig. 1. Flowchart of the proposed methodology describing each step for heart disease prediction. 3.1. Datasets In this research, two datasets named as cardiovascular disease (CVD) and Framingham were utilized to
Compared with a single indicator, the comprehensive indicators can improve the robustness, reliability, and accuracy of disease prediction. We visualized the distribution of the optimal features (Age, Gender, WHtR, MSP, Symptom, BT, Dentition, ECG, FBG, PLT, BUN) and emphasized the differences ...
Flowchart of Firefly algorithm [31] Full size image Fig. 7 Firefly algorithm [16] Full size image Comparatively, while traditional ensemble methods focus on model aggregation to improve prediction, our approach uniquely optimizes the input features using the firefly algorithm before model aggregation....
Study flowchart. Cases (n = 31) were male subjects from the GENES study (n = 834) who experienced a Coronary Heart Disease (CHD) events during the follow-up period (11.9 ± 4.1 years). The control subjects (n = 31), matched for age and date of recruitment, were...
The quantitative effects of congenital heart disease (CHD) risk factors are not fully understood. We conducted a meta-analysis of all CHD risk factors. This report explores maternal medication, assisted reproductive technologies (ART), and familial and fetal factors. Methods Relevant studies were iden...
The flowchart of the TLBO-FWNN method. 5. The Heart Disease Dataset The Cleveland heart disease dataset was obtained from the Cleveland Clinic Foundation, collected by Robert Detrano. This data was used to predict the presence or the absence of heart disease. It includes 303 instances, but on...
Heart disease is a common disease affecting human health. Electrocardiogram (ECG) classification is the most effective and direct method to detect heart disease, which is helpful to the diagnosis of most heart disease symptoms. At present, most ECG diagnosis depends on the personal judgment of medi...
Coronary heart disease (CHD) is the leading cause of death among adults in Germany. There is evidence that occupational exposure to particulate matter, noise, psychosocial stressors, shift work and high physical workload are associated with CHD. The aim
3.3. Heart Disease Identification Flowchart ECG signals can more intuitively reflect abnormal cardiac activity, and the HRV values extracted from ECG signals can effectively indicate these abnormalities. Therefore, this paper focuses on collecting ECG signals using portable devices, extracting HRV signals ...
and duration. The current study extended this previous effort using a different approach. Our weighted composite approach is optimized for accurate prediction of heart disease and could be used in future studies as the regression weights were derived from a relatively large and representative sample of...