Deep learning models for diagnosis of schizophrenia using EEG signals: emerging trends, challenges, and prospects
Schizophrenia (ScZ) is a chronic neuropsychiatric disorder characterized by disruptions in
cognitive, perceptual, social, emotional, and behavioral functions. In the traditional …
cognitive, perceptual, social, emotional, and behavioral functions. In the traditional …
Boosting motor imagery brain-computer interface classification using multiband and hybrid feature extraction
Brain-computer interface (BCI) is a new promising technology for control and
communication, the BCI system aims to decode the measured brain activity into a command …
communication, the BCI system aims to decode the measured brain activity into a command …
A new approach for gastrointestinal tract findings detection and classification: Deep learning-based hybrid stacking ensemble models
Endoscopic procedures for diagnosing gastrointestinal tract findings depend on specialist
experience and inter-observer variability. This variability can cause minor lesions to be …
experience and inter-observer variability. This variability can cause minor lesions to be …
A novel approach to schizophrenia Detection: Optimized preprocessing and deep learning analysis of multichannel EEG data
S Srinivasan, SD Johnson - Expert Systems with Applications, 2024 - Elsevier
Schizophrenia diagnosis, characterized by cognitive deficits, hallucinations, and delusions,
poses challenges due to its complex nature. Electroencephalogram (EEG) signals provide …
poses challenges due to its complex nature. Electroencephalogram (EEG) signals provide …
Systematic Literature Review: An Early Detection for Schizophrenia Classification Using Machine Learning Algorithms
AS Azizi, MM Kamal, N Azizan, RM Zawawi… - … : International Journal on …, 2024 - joiv.org
Schizophrenia is a complex mental health disorder that poses significant challenges in
diagnosis and treatment due to its multifaceted symptoms, such as hallucinations, delusions …
diagnosis and treatment due to its multifaceted symptoms, such as hallucinations, delusions …
[HTML][HTML] Midwifery learning and forecasting: Predicting content demand with user-generated logs
A Guitart, AF Del Río, Á Periáñez… - Artificial Intelligence in …, 2023 - Elsevier
Every day, 800 women and 6700 newborns die from complications related to pregnancy or
childbirth. A well-trained midwife can prevent most of these maternal and newborn deaths …
childbirth. A well-trained midwife can prevent most of these maternal and newborn deaths …
[HTML][HTML] Psychiatric disorders from EEG signals through deep learning models
Psychiatric disorders present diagnostic challenges due to individuals concealing their
genuine emotions, and traditional methods relying on neurophysiological signals have …
genuine emotions, and traditional methods relying on neurophysiological signals have …
[引用][C] MAC: Epilepsy EEG signal recognition based on the MLP-self-attention model and cosine distance
P Li, Y Liu, W Cai, X Liu - Journal of Mechanics in Medicine and …, 2024 - World Scientific
In current epilepsy disease research, accurate identification of epilepsy
electroencephalogram (EEG) signals is crucial for improving diagnostic efficiency and …
electroencephalogram (EEG) signals is crucial for improving diagnostic efficiency and …