[PDF][PDF] Performance Evaluation and Comparative Analysis of Different Machine Learning Algorithms in Predicting Cardiovascular Disease.
This study focuses on investigating the performance of different machine learning algorithms
and corresponding comparative analysis in predicting cardiovascular disease. Globally this …
and corresponding comparative analysis in predicting cardiovascular disease. Globally this …
Phonocardiogram signal processing for automatic diagnosis of congenital heart disorders through fusion of temporal and cepstral features
Congenital heart disease (CHD) is a heart disorder associated with the devastating
indications that result in increased mortality, increased morbidity, increased healthcare …
indications that result in increased mortality, increased morbidity, increased healthcare …
Automatic seizure detection by convolutional neural networks with computational complexity analysis
Abstract Background and Objectives Nowadays, an automated computer-aided diagnosis
(CAD) is an approach that plays an important role in the detection of health issues. The main …
(CAD) is an approach that plays an important role in the detection of health issues. The main …
A hybrid deep transfer learning-based approach for Parkinson's disease classification in surface electromyography signals
K Rezaee, S Savarkar, X Yu, J Zhang - Biomedical Signal Processing and …, 2022 - Elsevier
Parkinson's disease (PD) is known as a rampant neurodegenerative disorder, which has
afflicted approximately 10 million people throughout the world. Surface Electromyography …
afflicted approximately 10 million people throughout the world. Surface Electromyography …
A hybrid stacked CNN and residual feedback GMDH-LSTM deep learning model for stroke prediction applied on mobile AI smart hospital platform
BM Elbagoury, L Vladareanu, V Vlădăreanu, AB Salem… - Sensors, 2023 - mdpi.com
Artificial intelligence (AI) techniques for intelligent mobile computing in healthcare has
opened up new opportunities in healthcare systems. Combining AI techniques with the …
opened up new opportunities in healthcare systems. Combining AI techniques with the …
ECG-based biometric authentication using empirical mode decomposition and support vector machines
Electrocardiogram (ECG) is an electric signal of cardiac activity posing highly discriminative
properties related to human recognition. ECG based authentication has gained much …
properties related to human recognition. ECG based authentication has gained much …
Electricity theft detection using empirical mode decomposition and K-nearest neighbors
Electricity theft is a criminal practice of stealing electricity. In the country like Pakistan where
the consumption is more than the production, the electricity theft can be hazardous for the …
the consumption is more than the production, the electricity theft can be hazardous for the …
Characterization of term and preterm deliveries using electrohysterograms signatures
Preterm birth is the leading cause defining the infant mortality and morbidity globally. Non-
invasive surface uterine electromyogram (sEMG) also known as Electrohysterogram (EHG) …
invasive surface uterine electromyogram (sEMG) also known as Electrohysterogram (EHG) …
An automated system towards diagnosis of pneumonia using pulmonary auscultations
Respiratory sounds carry significant information about the condition of respiratory system.
Respiratory sounds are often affected by sounds emanating from heart and other organs …
Respiratory sounds are often affected by sounds emanating from heart and other organs …
A novel embedded system design for the detection and classification of cardiac disorders
Phonocardiogram (PCG) signals hold significant prognostic and diagnostic information
about cardiac health. Numerous PCG or heart sound based automated detection algorithms …
about cardiac health. Numerous PCG or heart sound based automated detection algorithms …