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 …
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 …
require human intelligence, such as visual perception, speech recognition, decision-making …
The significance of machine learning in clinical disease diagnosis: A review
The global need for effective disease diagnosis remains substantial, given the complexities
of various disease mechanisms and diverse patient symptoms. To tackle these challenges …
of various disease mechanisms and diverse patient symptoms. To tackle these challenges …
[HTML][HTML] From machine learning to deep learning: An advances of the recent data-driven paradigm shift in medicine and healthcare
The medicine and healthcare sector has been evolving and advancing very fast. The
advancement has been initiated and shaped by the applications of data-driven, robust, and …
advancement has been initiated and shaped by the applications of data-driven, robust, and …
Explainable artificial intelligence (XAI) with IoHT for smart healthcare: A review
Discussing the use of artificial intelligence (AI) in healthcare, explainability is a highly
contentious topic. AI-powered systems may be superior at certain analytical tasks, but their …
contentious topic. AI-powered systems may be superior at certain analytical tasks, but their …
A methodological and theoretical framework for implementing explainable artificial intelligence (XAI) in business applications
Artificial Intelligence (AI) is becoming fundamental in almost all activity sectors in our society.
However, most of the modern AI techniques (eg, Machine Learning–ML) have a black box …
However, most of the modern AI techniques (eg, Machine Learning–ML) have a black box …
Security aspects in IoT based cloud computing
Cloud computing offers a flexible framework in which data and resources are spread across
different locations and can be accessed from various industrial environments. This …
different locations and can be accessed from various industrial environments. This …
[PDF][PDF] Explainable AI in Healthcare: Enhancing transparency and trust upon legal and ethical consideration
As artificial intelligence (AI) continues to make significant advancements in healthcare, there
is a growing need to ensure the transparency and trustworthiness of AI-driven clinical …
is a growing need to ensure the transparency and trustworthiness of AI-driven clinical …
Population characteristic exploitation-based multi-orientation multi-objective gene selection for microarray data classification
M Li, R Cao, Y Zhao, Y Li, S Deng - Computers in Biology and Medicine, 2024 - Elsevier
Gene selection is a process of selecting discriminative genes from microarray data that
helps to diagnose and classify cancer samples effectively. Swarm intelligence evolution …
helps to diagnose and classify cancer samples effectively. Swarm intelligence evolution …
Rethinking densely connected convolutional networks for diagnosing infectious diseases
Due to its high transmissibility, the COVID-19 pandemic has placed an unprecedented
burden on healthcare systems worldwide. X-ray imaging of the chest has emerged as a …
burden on healthcare systems worldwide. X-ray imaging of the chest has emerged as a …