Deep learning for anomaly detection in multivariate time series: Approaches, applications, and challenges
Anomaly detection has recently been applied to various areas, and several techniques
based on deep learning have been proposed for the analysis of multivariate time series. In …
based on deep learning have been proposed for the analysis of multivariate time series. In …
A review on software and hardware developments in automatic epilepsy diagnosis using EEG datasets
Epilepsy is a common non‐communicable, group of neurological disorders affecting more
than 50 million individuals worldwide. Different approaches of basic, clinical, and …
than 50 million individuals worldwide. Different approaches of basic, clinical, and …
Automatic epileptic seizure detection based on persistent homology
Z Wang, F Liu, S Shi, S Xia, F Peng, L Wang… - Frontiers in …, 2023 - frontiersin.org
Epilepsy is a prevalent brain disease, which is quite difficult-to-treat or cure. This study
developed a novel automatic seizure detection method based on the persistent homology …
developed a novel automatic seizure detection method based on the persistent homology …
EEG Datasets in Machine Learning Applications of Epilepsy Diagnosis and Seizure Detection
Epilepsy is a common non-communicable, group of neurological disorders affecting more
than 50 million individuals worldwide. Researchers are working to automatically detect …
than 50 million individuals worldwide. Researchers are working to automatically detect …
Software advancements in automatic epilepsy diagnosis and seizure detection: 10-year review
Epilepsy is a chronic neurological disorder that may be diagnosed and monitored using
routine diagnostic tests like Electroencephalography (EEG). However, manual introspection …
routine diagnostic tests like Electroencephalography (EEG). However, manual introspection …
Automatic classification of normal/AD brain MRI slices using whale-algorithm optimized hybrid image features
S Kadry, VE Jessy, V Rajinikanth… - Journal of Ambient …, 2023 - Springer
In recent years, the prevalence of Age-Related Illnesses (ARL) has been increasing among
older individuals, and early recognition and treatment will result in better living conditions. It …
older individuals, and early recognition and treatment will result in better living conditions. It …
Framework for Healthy/Hemorrhagic Brain Condition Detection using CT Scan Images
S Kadry, AH Gandomi - Proceedings of the 2023 7th International …, 2023 - dl.acm.org
In human physiology, the brain plays a significant role as the control center of all regulatory
processes. Any abnormality in the brain could lead to various physiological and …
processes. Any abnormality in the brain could lead to various physiological and …
Positional multi-length and mutual-attention network for epileptic seizure classification
G Zhang, A Zhang, H Liu, J Luo, J Chen - Frontiers in Computational …, 2024 - frontiersin.org
The automatic classification of epilepsy electroencephalogram (EEG) signals plays a crucial
role in diagnosing neurological diseases. Although promising results have been achieved …
role in diagnosing neurological diseases. Although promising results have been achieved …
Serially Fused Dual-Deep-Features Based Chest X-Ray Classification Scheme to Detect Tuberculosis
In hospitals, the increased frequency of disease occurrence has resulted in an increased
diagnostic burden; therefore, several semi/fully automatic disease detection systems have …
diagnostic burden; therefore, several semi/fully automatic disease detection systems have …
Pedestrian Trajectory Prediction and Pose Estimation Considering Behavioral Characteristic Relationships and Noise Inhibition
J Zhou, W Fu, B Ning, S He - IEEE Access, 2024 - ieeexplore.ieee.org
In the domain of pedestrian trajectory prediction (PTP) from a roadbed perspective, the
visibility of pedestrian feature points is inevitably compromised by external noise …
visibility of pedestrian feature points is inevitably compromised by external noise …