Emotion recognition in EEG signals using deep learning methods: A review

M Jafari, A Shoeibi, M Khodatars… - Computers in Biology …, 2023 - Elsevier
Emotions are a critical aspect of daily life and serve a crucial role in human decision-making,
planning, reasoning, and other mental states. As a result, they are considered a significant …

Privacy and security concerns in generative AI: a comprehensive survey

A Golda, K Mekonen, A Pandey, A Singh… - IEEE …, 2024 - ieeexplore.ieee.org
Generative Artificial Intelligence (GAI) has sparked a transformative wave across various
domains, including machine learning, healthcare, business, and entertainment, owing to its …

Generative artificial intelligence

L Banh, G Strobel - Electronic Markets, 2023 - Springer
Recent developments in the field of artificial intelligence (AI) have enabled new paradigms
of machine processing, shifting from data-driven, discriminative AI tasks toward …

Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review

A Shoeibi, M Khodatars, M Jafari, N Ghassemi… - Information …, 2023 - Elsevier
Brain diseases, including tumors and mental and neurological disorders, seriously threaten
the health and well-being of millions of people worldwide. Structural and functional …

[HTML][HTML] Application of computational biology and artificial intelligence in drug design

Y Zhang, M Luo, P Wu, S Wu, TY Lee, C Bai - International journal of …, 2022 - mdpi.com
Traditional drug design requires a great amount of research time and developmental
expense. Booming computational approaches, including computational biology, computer …

Multi-disease prediction based on deep learning: a survey

S **e, Z Yu, Z Lv - Computer Modeling in Engineering & …, 2021 - ingentaconnect.com
In recent years, the development of artificial intelligence (AI) and the gradual beginning of
AI's research in the medical field have allowed people to see the excellent prospects of the …

[HTML][HTML] Multiple instance learning for digital pathology: A review of the state-of-the-art, limitations & future potential

M Gadermayr, M Tschuchnig - Computerized Medical Imaging and …, 2024 - Elsevier
Digital whole slides images contain an enormous amount of information providing a strong
motivation for the development of automated image analysis tools. Particularly deep neural …

Empowering precision medicine: AI-driven schizophrenia diagnosis via EEG signals: A comprehensive review from 2002–2023

M Jafari, D Sadeghi, A Shoeibi, H Alinejad-Rokny… - Applied …, 2024 - Springer
Schizophrenia (SZ) is a prevalent mental disorder characterized by cognitive, emotional,
and behavioral changes. Symptoms of SZ include hallucinations, illusions, delusions, lack of …

A survey on variational autoencoders from a green AI perspective

A Asperti, D Evangelista, E Loli Piccolomini - SN Computer Science, 2021 - Springer
Abstract Variational Autoencoders (VAEs) are powerful generative models that merge
elements from statistics and information theory with the flexibility offered by deep neural …

Extraction and recovery of spatio-temporal structure in latent dynamics alignment with diffusion models

Y Wang, Z Wu, C Li, A Wu - Advances in Neural Information …, 2023 - proceedings.neurips.cc
In the field of behavior-related brain computation, it is necessary to align raw neural signals
against the drastic domain shift among them. A foundational framework within neuroscience …