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A decision support system for heart disease prediction based upon machine learning
Detection of heart disease through early-stage symptoms is a great challenge in the current
world scenario. If not diagnosed timely then this may become the cause of death. In …
world scenario. If not diagnosed timely then this may become the cause of death. In …
A hybrid system for Parkinson's disease diagnosis using machine learning techniques
Parkinson's disease is a neurodegenerative disorder that progresses slowly and its
symptoms appear over time, so its early diagnosis is not easy. A neurologist can diagnose …
symptoms appear over time, so its early diagnosis is not easy. A neurologist can diagnose …
A smart decision support system to diagnose arrhythymia using ensembled ConvNet and ConvNet-LSTM model
Automatic screening approaches can help diagnose Cardiovascular Disease (CVD) early,
which is the leading source of mortality worldwide. Electrocardiogram (ECG/EKG)-based …
which is the leading source of mortality worldwide. Electrocardiogram (ECG/EKG)-based …
Phonocardiogram signal based multi-class cardiac diagnostic decision support system
A Phonocardiogram (PCG) signal represents murmurs and sounds signals made by
vibrations caused for the period of a cardiac cycle. Acoustic wave generated through the …
vibrations caused for the period of a cardiac cycle. Acoustic wave generated through the …
[PDF][PDF] Machine learning-based model for prediction of power consumption in smart grid.
An electric grid consists of transformers, generation centers, communication links, control
stations, and distributors. Collectively these components help in moving power from one …
stations, and distributors. Collectively these components help in moving power from one …
A hybrid approach for feature selection based on genetic algorithm and recursive feature elimination
Abstract Machine learning has become an integral part of our life in today's world. Machine
learning when applied to real-world applications suffers from the problem of high …
learning when applied to real-world applications suffers from the problem of high …
HIOC: a hybrid imputation method to predict missing values in medical datasets
Purpose Decision support systems developed using machine learning classifiers have
become a valuable tool in predicting various diseases. However, the performance of these …
become a valuable tool in predicting various diseases. However, the performance of these …
Deep Learning and Transfer Learning in Cardiology: A Review of Cardiovascular Disease Prediction Models
Cardiovascular disorders are the primary cause of death on a global scale. The World
Health Organization report indicates that approximately 18 million people die from CVD …
Health Organization report indicates that approximately 18 million people die from CVD …
An improved hybrid model for cardiovascular disease detection using machine learning in IoT
Cardiovascular disease (CVD) believes to be a major cause of transience and indisposition
worldwide. Early diagnosis and timely intervention are critical in preventing the progression …
worldwide. Early diagnosis and timely intervention are critical in preventing the progression …
Coronary artery disease diagnosis using extra tree-support vector machine: ET-SVMRBF
Coronary Artery Disease (CAD) is a type of cardiovascular disease that can lead to cardiac
arrest if not diagnosed timely. Angiography is a standard method adopted to diagnose CAD …
arrest if not diagnosed timely. Angiography is a standard method adopted to diagnose CAD …