Machine learning techniques for diagnosis of alzheimer disease, mild cognitive disorder, and other types of dementia

G Mirzaei, H Adeli - Biomedical Signal Processing and Control, 2022‏ - Elsevier
Alzheimer's disease (AD) is one of the most common form of dementia which mostly affects
elderly people. AD identification in early stages is a difficult task in medical practice and …

Self-supervised learning for electroencephalography

MH Rafiei, LV Gauthier, H Adeli… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
Decades of research have shown machine learning superiority in discovering highly
nonlinear patterns embedded in electroencephalography (EEG) records compared with …

An attention-aware long short-term memory-like spiking neural model for sentiment analysis

Q Liu, Y Huang, Q Yang, H Peng… - International journal of …, 2023‏ - World Scientific
LSTM-SNP model is a recently developed long short-term memory (LSTM) network, which is
inspired from the mechanisms of spiking neural P (SNP) systems. In this paper, LSTM-SNP …

Predicting blood–brain barrier permeability of molecules with a large language model and machine learning

ETC Huang, JS Yang, KYK Liao, WCW Tseng… - Scientific Reports, 2024‏ - nature.com
Predicting the blood–brain barrier (BBB) permeability of small-molecule compounds using a
novel artificial intelligence platform is necessary for drug discovery. Machine learning and a …

Facial expression recognition with contrastive learning and uncertainty-guided relabeling

Y Yang, L Hu, C Zu, Q Zhou, X Wu, J Zhou… - International Journal of …, 2023‏ - World Scientific
Facial expression recognition (FER) plays a vital role in the field of human-computer
interaction. To achieve automatic FER, various approaches based on deep learning (DL) …

A hybrid time-distributed deep neural architecture for speech emotion recognition

J De Lope, M Grana - International journal of neural systems, 2022‏ - World Scientific
In recent years, speech emotion recognition (SER) has emerged as one of the most active
human–machine interaction research areas. Innovative electronic devices, services and …

Emotion classification from EEG with a low-cost BCI versus a high-end equipment

R Sánchez-Reolid, MC Martínez-Sáez… - … journal of neural …, 2022‏ - World Scientific
The assessment of physiological signals such as the electroencephalography (EEG) has
become a key point in the research area of emotion detection. This study compares the …

Unlocking travel narratives: a fusion of stacking ensemble deep learning and neural topic modeling for enhanced tourism comment analysis

N Habbat, H Nouri - Social Network Analysis and Mining, 2024‏ - Springer
User-generated comments are crucial in the domain of hotel bookings, especially in the fast-
changing online planning and booking industry. Our research presents a sophisticated …

Effect of action units, viewpoint and immersion on emotion recognition using dynamic virtual faces

MA Vicente-Querol, A Fernández-Caballero… - … Journal of Neural …, 2023‏ - World Scientific
Facial affect recognition is a critical skill in human interactions that is often impaired in
psychiatric disorders. To address this challenge, tests have been developed to measure and …

From intricacy to conciseness: A progressive transfer strategy for EEG-based cross-subject emotion recognition

Z Cai, L Wang, M Guo, G Xu, L Guo… - International Journal of …, 2022‏ - World Scientific
Emotion plays a significant role in human daily activities, and it can be effectively recognized
from EEG signals. However, individual variability limits the generalization of emotion …