Emotion recognition in EEG signals using deep learning methods: A review
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 …
planning, reasoning, and other mental states. As a result, they are considered a significant …
Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review
Brain diseases, including tumors and mental and neurological disorders, seriously threaten
the health and well-being of millions of people worldwide. Structural and functional …
the health and well-being of millions of people worldwide. Structural and functional …
Generative artificial intelligence
Recent developments in the field of artificial intelligence (AI) have enabled new paradigms
of machine processing, shifting from data-driven, discriminative AI tasks toward …
of machine processing, shifting from data-driven, discriminative AI tasks toward …
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 …
AI's research in the medical field have allowed people to see the excellent prospects of the …
Application of computational biology and artificial intelligence in drug design
Traditional drug design requires a great amount of research time and developmental
expense. Booming computational approaches, including computational biology, computer …
expense. Booming computational approaches, including computational biology, computer …
[HTML][HTML] Multiple instance learning for digital pathology: A review of the state-of-the-art, limitations & future potential
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 …
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
Schizophrenia (SZ) is a prevalent mental disorder characterized by cognitive, emotional,
and behavioral changes. Symptoms of SZ include hallucinations, illusions, delusions, lack of …
and behavioral changes. Symptoms of SZ include hallucinations, illusions, delusions, lack of …
A survey on variational autoencoders from a green AI perspective
Abstract Variational Autoencoders (VAEs) are powerful generative models that merge
elements from statistics and information theory with the flexibility offered by deep neural …
elements from statistics and information theory with the flexibility offered by deep neural …
Knowledge Extraction from PV Power Generation with Deep Learning Autoencoder and Clustering-Based Algorithms
The unpredictable nature of photovoltaic solar power generation, caused by changing
weather conditions, creates challenges for grid operators as they work to balance supply …
weather conditions, creates challenges for grid operators as they work to balance supply …
[HTML][HTML] Artificial intelligence and machine learning applications for cultured meat
Cultured meat has the potential to provide a complementary meat industry with reduced
environmental, ethical, and health impacts. However, major technological challenges …
environmental, ethical, and health impacts. However, major technological challenges …