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 …

Explainable artificial intelligence (XAI): concepts and challenges in healthcare

T Hulsen - AI, 2023 - mdpi.com
Artificial Intelligence (AI) describes computer systems able to perform tasks that normally
require human intelligence, such as visual perception, speech recognition, decision-making …

Towards building multilingual language model for medicine

P Qiu, C Wu, X Zhang, W Lin, H Wang, Y Zhang… - Nature …, 2024 - nature.com
The development of open-source, multilingual medical language models can benefit a wide,
linguistically diverse audience from different regions. To promote this domain, we present …

Case reports in neuroimaging and stimulation

S Battaglia, A Schmidt, S Hassel, M Tanaka - Frontiers in psychiatry, 2023 - frontiersin.org
The brain, a remarkable and intricate system, plays a fundamental role in sha** our
behavior, encompassing cognitive and emotional processes (1–3). Understanding its …

Insights into structural and functional organization of the brain: evidence from neuroimaging and non-invasive brain stimulation techniques

M Tanaka, M Diano, S Battaglia - Frontiers in Psychiatry, 2023 - frontiersin.org
The brain is a complex and dynamic system that underlies our behavior, emotions, and
cognition (1–3). To better understand the structural and functional organization of the brain …

Interpretability research of deep learning: A literature survey

B Xua, G Yang - Information Fusion, 2024 - Elsevier
Deep learning (DL) has been widely used in various fields. However, its black-box nature
limits people's understanding and trust in its decision-making process. Therefore, it becomes …

Diagnostic reasoning prompts reveal the potential for large language model interpretability in medicine

T Savage, A Nayak, R Gallo, E Rangan… - NPJ Digital Medicine, 2024 - nature.com
One of the major barriers to using large language models (LLMs) in medicine is the
perception they use uninterpretable methods to make clinical decisions that are inherently …

Exploring the intersection of artificial intelligence and clinical healthcare: a multidisciplinary review

CS Stafie, IG Sufaru, CM Ghiciuc, II Stafie, EC Sufaru… - Diagnostics, 2023 - mdpi.com
Artificial intelligence (AI) plays a more and more important role in our everyday life due to the
advantages that it brings when used, such as 24/7 availability, a very low percentage of …

Explaining the mechanism of multiscale groundwater drought events: A new perspective from interpretable deep learning model

H Cai, H Shi, Z Zhou, S Liu… - Water Resources …, 2024 - Wiley Online Library
This study presents a new approach to understand the causes of groundwater drought
events with interpretable deep learning (DL) models. As prerequisites, accurate long short …

A review of the explainability and safety of conversational agents for mental health to identify avenues for improvement

S Sarkar, M Gaur, LK Chen, M Garg… - Frontiers in Artificial …, 2023 - frontiersin.org
Virtual Mental Health Assistants (VMHAs) continuously evolve to support the overloaded
global healthcare system, which receives approximately 60 million primary care visits and 6 …