[HTML][HTML] Application of data fusion for automated detection of children with developmental and mental disorders: A systematic review of the last decade
Mental health is a basic need for a sustainable and developing society. The prevalence and
financial burden of mental illness have increased globally, and especially in response to …
financial burden of mental illness have increased globally, and especially in response to …
Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review
Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor
problems for people with a detrimental effect on the functioning of the nervous system. In …
problems for people with a detrimental effect on the functioning of the nervous system. In …
Deep learning for neuroimaging-based diagnosis and rehabilitation of autism spectrum disorder: a review
Abstract Accurate diagnosis of Autism Spectrum Disorder (ASD) followed by effective
rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) …
rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) …
An uncertainty-aware transfer learning-based framework for COVID-19 diagnosis
A Shamsi, H Asgharnezhad… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
The early and reliable detection of COVID-19 infected patients is essential to prevent and
limit its outbreak. The PCR tests for COVID-19 detection are not available in many countries …
limit its outbreak. The PCR tests for COVID-19 detection are not available in many countries …
Decision tree-based diagnosis of coronary artery disease: CART model
Abstract Background and Objective As the most common cardiovascular defect, coronary
artery disease (CAD), also called ischemic heart disease, is one of the substantial causes of …
artery disease (CAD), also called ischemic heart disease, is one of the substantial causes of …
Towards diagnostic aided systems in coronary artery disease detection: a comprehensive multiview survey of the state of the art
Introduction. Coronary artery disease (CAD) is one of the main causes of death all over the
world. One way to reduce the mortality rate from CAD is to predict its risk and take effective …
world. One way to reduce the mortality rate from CAD is to predict its risk and take effective …
Enhanced deep learning assisted convolutional neural network for heart disease prediction on the internet of medical things platform
Y Pan, M Fu, B Cheng, X Tao, J Guo - Ieee Access, 2020 - ieeexplore.ieee.org
The diagnosis of heart disease has become a difficult medical task in the present medical
research. This diagnosis depends on the detailed and precise analysis of the patient's …
research. This diagnosis depends on the detailed and precise analysis of the patient's …
Automated detection of coronary artery disease, myocardial infarction and congestive heart failure using GaborCNN model with ECG signals
Cardiovascular diseases (CVDs) are main causes of death globally with coronary artery
disease (CAD) being the most important. Timely diagnosis and treatment of CAD is crucial to …
disease (CAD) being the most important. Timely diagnosis and treatment of CAD is crucial to …
[HTML][HTML] Handling of uncertainty in medical data using machine learning and probability theory techniques: A review of 30 years (1991–2020)
Understanding the data and reaching accurate conclusions are of paramount importance in
the present era of big data. Machine learning and probability theory methods have been …
the present era of big data. Machine learning and probability theory methods have been …
Heart disease prediction using hyper parameter optimization (HPO) tuning
R Valarmathi, T Sheela - Biomedical Signal Processing and Control, 2021 - Elsevier
Coronary artery disease prediction is considered to be one of the most challenging tasks in
the health care industry. In our research, we propose a prediction system to detect the heart …
the health care industry. In our research, we propose a prediction system to detect the heart …