The most current research demonstrates the various methods used to increase heart disease prediction accuracy. Researchers have made tremendous progress in improving the precision and effectiveness of prediction models through the use of ensemble learning28, feature extraction29, DL models30, and other te...
This research employs health monitoring systems for heart patients using IoT and AI-based solutions. Activities of heart patients are monitored and reported using the IoT system. For heart disease prediction, an ensemble model ET-CNN is presented which provides an accuracy score of 0.9524. The ...
Cardiovascular disease is the most important disease of the heart, and the stage of the disease is diagnosed, the disease can be diagnosed anytime. The following method is used to find out its status. The heart disease prediction is based on Bagging Ensemble Technique with Dee...
Heart disease includes many kinds of conditions affecting the heart and has been the main cause of death worldwide in recent decades. To prevent further da
Electrocardiogram (ECG) signals represent the electrical activity of the human hearts and consist of several waveforms (P, QRS, and T). The duration and shape of each waveform and the distances between different peaks are used to diagnose heart diseases.
AutoML; machine learning; cardiovascular disease; coronary artery disease; diagnosis; heart disease; prediction; AutoGluon; AutoKeras; PyCaret1. Introduction The term “cardiovascular disease” (CVD) applies to any disorder affecting the cardiovascular system (heart and blood vessels) [1]. Over 17 ...
UCI. Heart Disease Data Set. Available online: https://www.kaggle.com/datasets/redwankarimsony/heart-disease-data (accessed on 1 November 2022). Ishaq, A.; Sadiq, S.; Umer, M.; Ullah, S.; Mirjalili, S.; Rupapara, V.; Nappi, M. Improving the prediction of heart failure patients’...
Heart failure: Diagnosis, severity estimation and prediction of adverse events through machine learning techniques. Comput. Struct. Biotechnol. J. 2017, 15, 26–47. [Google Scholar] [CrossRef] [Green Version] Chandra, B.S.; Sastry, C.S.; Jana, S. Robust heartbeat detection from multimodal...