Modified Self-Adaptive Bayesian algorithm for smart heart disease prediction in IoT system
Heart disease (HD) has surpassed all other causes of death in recent years. Estimating
one's risk of developing heart disease is difficult, since it takes both specialized knowledge …
one's risk of developing heart disease is difficult, since it takes both specialized knowledge …
A hybrid model for heart disease prediction using recurrent neural network and long short term memory
GS Bhavekar, AD Goswami - International Journal of Information …, 2022 - Springer
Cardiac and cardiovascular diseases are among the most prevalent and dangerous
ailments that influence human health. The detection of cardiac disease in its early stages by …
ailments that influence human health. The detection of cardiac disease in its early stages by …
A Comparative Study of Machine Learning classifiers to analyze the Precision of Myocardial Infarction prediction
RH Khan, J Miah, SAA Nipun… - 2023 IEEE 13th Annual …, 2023 - ieeexplore.ieee.org
In the modern world, heart disease ranks among the main causes of death. Smoking, high
blood pressure, and cholesterol are the three key risk factors for getting one heart disease …
blood pressure, and cholesterol are the three key risk factors for getting one heart disease …
A smart IoT-enabled heart disease monitoring system using meta-heuristic-based Fuzzy-LSTM model
A continuous heart disease monitoring system is one of the significant applications specified
by the Internet of Things (IoT). This goal might be achieved by combining sophisticated …
by the Internet of Things (IoT). This goal might be achieved by combining sophisticated …
Improving Cardiovascular Disease Prediction Through Comparative Analysis of Machine Learning Models: A Case Study on Myocardial Infarction
Cardiovascular disease remains a leading cause of mortality in the contemporary world. Its
association with smoking, elevated blood pressure, and cholesterol levels underscores the …
association with smoking, elevated blood pressure, and cholesterol levels underscores the …
Heart disease prediction using machine learning and deep learning algorithms
K Vayadande, R Golawar, S Khairnar… - 2022 international …, 2022 - ieeexplore.ieee.org
WHO reports states which are nearly 1 crore 20 lakhs deaths happen due to heart diseases.
In past years heart disease or cardiovascular disease cause large impact in medical …
In past years heart disease or cardiovascular disease cause large impact in medical …
A Review: Machine Learning and Data Mining Approaches for Cardiovascular Disease Diagnosis and Prediction
GS Rao, G Muneeswari - EAI Endorsed Transactions on …, 2024 - publications.eai.eu
INTRODUCTION: Cardiovascular disease (CVD) is the most common cause of death
worldwide, and its prevalence is rising in low-resource settings and among those with lower …
worldwide, and its prevalence is rising in low-resource settings and among those with lower …
MDensNet201-IDRSRNet: Efficient cardiovascular disease prediction system using hybrid deep learning
M Mandava - Biomedical Signal Processing and Control, 2024 - Elsevier
Cardiovascular diseases (CVDs) are common diseases that impact the heart or vascular
system. Since early discovery significantly improves survival chances, precise prediction …
system. Since early discovery significantly improves survival chances, precise prediction …
Heart Disease Prediction using Ensemble ML
Worldwide, heart disease is one of the main causes of mortality. Heart disease early
identification and prevention can significantly enhance patient outcomes and save …
identification and prevention can significantly enhance patient outcomes and save …
ElGamal homomorphic encryption-based privacy preserving association rule mining on horizontally partitioned healthcare data
N Domadiya, UP Rao - Journal of The Institution of Engineers (India) …, 2022 - Springer
In today's world, life-threatening diseases have become a pre-eminent issue in healthcare
due to the higher mortality rate. It is possible to lower this mortality rate by utilizing …
due to the higher mortality rate. It is possible to lower this mortality rate by utilizing …