Cardiovascular diseases are responsible for one-third of all deaths that occur globally. Machine learning and data mining have made it easier and quicker for physicians to diagnose or identify patients. This article presents a novel late fusion metho...
Cardiovascular disorders (heart diseases) are the most prevalent cause of death on a global scale. So early detection and classification increase the likelihood of survival. In the context of machine learning techniques, there is always a need for an...
The medical community demands accurate predictive models for early heart disease diagnosis because heart disease remains a significant worldwide health concern. Deep learning research presents a predictive system for heart disease that uses K-mode cl...
BACKGROUND: Emergency department (ED) crowding is often attributed to a slow hospitalization process, leading to reduced quality of care. Predicting early disposition in patients presenting with cardiac issues is challenging: most are ultimately disc...
In health care, an accurate diagnosis with the help of a data-driven forecasting framework takes the risk factors associated with heart disease. However, building such an effective model using deep learning (DL) methods requires high-quality data, i....
With cardiovascular diseases accounting for all other causes of mortality worldwide, an increasing proportion of individuals are being treated for them. To identify the cardiac issue, medical practitioners have to examine electrocardiogram (ECG) data...
Heart disease continues to rank among the world's top causes of death, underscoring the pressing need for precise and accurate prediction techniques. Performance issues with traditional machine learning techniques have been identified, particularly w...
BACKGROUND: Dyspnea is a common cause of hospitalization, posing diagnostic challenges among older adult patients with multimorbid conditions. Chest computed tomography (CT) scans are increasingly used in patients with dyspnea and offer superior diag...
Cardiovascular illnesses continue to be a predominant cause of mortality globally, underscoring the necessity for prompt and precise diagnosis to mitigate consequences and healthcare expenditures. This work presents a complete hybrid methodology that...
INTRODUCTION: Heart Disease (HD) stands as the foremost reason for mortality all over the world for both men and women. Millions of people are affected worldwide every year, resulting in numerous fatalities. Timely and precise detection is essential ...
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