Neural decoding of EEG signals with machine learning: a systematic review
Electroencephalography (EEG) is a non-invasive technique used to record the brain's
evoked and induced electrical activity from the scalp. Artificial intelligence, particularly …
evoked and induced electrical activity from the scalp. Artificial intelligence, particularly …
[HTML][HTML] Medical deep learning—A systematic meta-review
Deep learning has remarkably impacted several different scientific disciplines over the last
few years. For example, in image processing and analysis, deep learning algorithms were …
few years. For example, in image processing and analysis, deep learning algorithms were …
Medical image analysis based on deep learning approach
M Puttagunta, S Ravi - Multimedia tools and applications, 2021 - Springer
Medical imaging plays a significant role in different clinical applications such as medical
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …
Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach: A review of two decades of research
Industry 4.0 is an era of smart manufacturing. Manufacturing is impossible without the use of
machinery. The majority of these machines comprise rotating components and are called …
machinery. The majority of these machines comprise rotating components and are called …
Diagnosing of disease using machine learning
The role of machine learning in the healthcare industry is inevitable due to its power to use
in disease detection and management. Disease diagnosis using machine-learning …
in disease detection and management. Disease diagnosis using machine-learning …
Deep learning for neurodegenerative disorder (2016 to 2022): A systematic review
J Chaki, M Woźniak - Biomedical Signal Processing and Control, 2023 - Elsevier
A neurodegenerative disorder, such as Parkinson's, Alzheimer's, epilepsy, stroke, and
others, is a type of disease in which central nervous system cells stop working or die …
others, is a type of disease in which central nervous system cells stop working or die …
Gait analysis in Parkinson's disease: An overview of the most accurate markers for diagnosis and symptoms monitoring
L Di Biase, A Di Santo, ML Caminiti, A De Liso… - Sensors, 2020 - mdpi.com
The aim of this review is to summarize that most relevant technologies used to evaluate gait
features and the associated algorithms that have shown promise to aid diagnosis and …
features and the associated algorithms that have shown promise to aid diagnosis and …
Artificial intelligence for brain diseases: A systematic review
Artificial intelligence (AI) is a major branch of computer science that is fruitfully used for
analyzing complex medical data and extracting meaningful relationships in datasets, for …
analyzing complex medical data and extracting meaningful relationships in datasets, for …
[HTML][HTML] A comprehensive survey of deep learning in the field of medical imaging and medical natural language processing: Challenges and research directions
B Pandey, DK Pandey, BP Mishra… - Journal of King Saud …, 2022 - Elsevier
The extensive growth of data in the health domain has increased the utility of Deep Learning
in health. Deep learning is a highly advanced successor of artificial neural networks, having …
in health. Deep learning is a highly advanced successor of artificial neural networks, having …
Artificial intelligence for Alzheimer's disease: promise or challenge?
Decades of experimental and clinical research have contributed to unraveling many
mechanisms in the pathogenesis of Alzheimer's disease (AD), but the puzzle is still …
mechanisms in the pathogenesis of Alzheimer's disease (AD), but the puzzle is still …