[HTML][HTML] Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond
Abstract Explainable Artificial Intelligence (XAI) is an emerging research topic of machine
learning aimed at unboxing how AI systems' black-box choices are made. This research field …
learning aimed at unboxing how AI systems' black-box choices are made. This research field …
Deep learning and medical diagnosis: A review of literature
M Bakator, D Radosav - Multimodal Technologies and Interaction, 2018 - mdpi.com
In this review the application of deep learning for medical diagnosis is addressed. A
thorough analysis of various scientific articles in the domain of deep neural networks …
thorough analysis of various scientific articles in the domain of deep neural networks …
Natural language processing advancements by deep learning: A survey
Natural Language Processing (NLP) helps empower intelligent machines by enhancing a
better understanding of the human language for linguistic-based human-computer …
better understanding of the human language for linguistic-based human-computer …
Recent advances in convolutional neural network acceleration
In recent years, convolutional neural networks (CNNs) have shown great performance in
various fields such as image classification, pattern recognition, and multi-media …
various fields such as image classification, pattern recognition, and multi-media …
Subsurface sedimentary structure identification using deep learning: A review
The reliable identification of subsurface sedimentary structures (ie, geologic heterogeneity)
is critical in various earth and environmental sciences, petroleum reservoir engineering, and …
is critical in various earth and environmental sciences, petroleum reservoir engineering, and …
Emotion recognition from EEG signals using recurrent neural networks
The application of electroencephalogram (EEG)-based emotion recognition (ER) to the brain–
computer interface (BCI) has become increasingly popular over the past decade. Emotion …
computer interface (BCI) has become increasingly popular over the past decade. Emotion …
Recent progress in the discovery and design of antimicrobial peptides using traditional machine learning and deep learning
Antimicrobial resistance has become a critical global health problem due to the abuse of
conventional antibiotics and the rise of multi-drug-resistant microbes. Antimicrobial peptides …
conventional antibiotics and the rise of multi-drug-resistant microbes. Antimicrobial peptides …
A survey on deep learning techniques in wireless signal recognition
X Li, F Dong, S Zhang, W Guo - Wireless Communications and …, 2019 - Wiley Online Library
Wireless signal recognition plays an important role in cognitive radio, which promises a
broad prospect in spectrum monitoring and management with the coming applications for …
broad prospect in spectrum monitoring and management with the coming applications for …
A novel multi-step ahead forecasting model for flood based on time residual LSTM
Y Zou, J Wang, P Lei, Y Li - Journal of Hydrology, 2023 - Elsevier
Climate change has significantly impacted hydrology, including extreme precipitation, and
changing precipitation patterns that could lead to an increase in flooding. Life and property …
changing precipitation patterns that could lead to an increase in flooding. Life and property …
Machine learning for bioelectronics on wearable and implantable devices: challenges and potential
Bioelectronics presents a promising future in the field of embedded and implantable
electronics, providing a range of functional applications, from personal health monitoring to …
electronics, providing a range of functional applications, from personal health monitoring to …