AI Medical Compendium Journal:
IEEE transactions on neural networks and learning systems

Showing 21 to 30 of 780 articles

Design and Implementation of Pavlovian Associative Memory Based on DNA Neurons.

IEEE transactions on neural networks and learning systems
In the field of biocomputing and neural networks, deoxyribonucleic acid (DNA) strand displacement (DSD) technology performs well in computation, programming, and information processing. In this article, the multiplication gate, addition gate, and thr...

Brain-Inspired Learning, Perception, and Cognition: A Comprehensive Review.

IEEE transactions on neural networks and learning systems
The progress of brain cognition and learning mechanisms has provided new inspiration for the next generation of artificial intelligence (AI) and provided the biological basis for the establishment of new models and methods. Brain science can effectiv...

Deep Geometric Learning With Monotonicity Constraints for Alzheimer's Disease Progression.

IEEE transactions on neural networks and learning systems
Alzheimer's disease (AD) is a devastating neurodegenerative condition that precedes progressive and irreversible dementia; thus, predicting its progression over time is vital for clinical diagnosis and treatment. For this, numerous studies have imple...

Learning an Autonomous Dynamic System to Encode Periodic Human Motion Skills.

IEEE transactions on neural networks and learning systems
Learning an autonomous dynamic system (ADS) encoding human motion rules has been shown as an effective way for human motion skills transfer. However, most existing approaches focus on goal-directed motion skills transfer, and the study on periodic mo...

RPI-GGCN: Prediction of RNA-Protein Interaction Based on Interpretability Gated Graph Convolution Neural Network and Co-Regularized Variational Autoencoders.

IEEE transactions on neural networks and learning systems
RNA-protein interactions (RPIs) play an important role in several fundamental cellular physiological processes, including cell motility, chromosome replication, transcription and translation, and signaling. Predicting RPI can guide the exploration of...

Communication-Efficient Hybrid Federated Learning for E-Health With Horizontal and Vertical Data Partitioning.

IEEE transactions on neural networks and learning systems
Electronic healthcare (e-health) allows smart devices and medical institutions to collaboratively collect patients' data, which is trained by artificial intelligence (AI) technologies to help doctors make diagnosis. By allowing multiple devices to tr...

Complex-Valued Convolutional Gated Recurrent Neural Network for Ultrasound Beamforming.

IEEE transactions on neural networks and learning systems
Ultrasound detection is a potent tool for the clinical diagnosis of various diseases due to its real-time, convenient, and noninvasive qualities. Yet, existing ultrasound beamforming and related methods face a big challenge to improve both the qualit...

Adaptive Synaptic Scaling in Spiking Networks for Continual Learning and Enhanced Robustness.

IEEE transactions on neural networks and learning systems
Synaptic plasticity plays a critical role in the expression power of brain neural networks. Among diverse plasticity rules, synaptic scaling presents indispensable effects on homeostasis maintenance and synaptic strength regulation. In the current mo...

A Generative Shape Compositional Framework to Synthesize Populations of Virtual Chimeras.

IEEE transactions on neural networks and learning systems
Generating virtual organ populations that capture sufficient variability while remaining plausible is essential to conduct in silico trials (ISTs) of medical devices. However, not all anatomical shapes of interest are always available for each indivi...

DER-GCN: Dialog and Event Relation-Aware Graph Convolutional Neural Network for Multimodal Dialog Emotion Recognition.

IEEE transactions on neural networks and learning systems
With the continuous development of deep learning (DL), the task of multimodal dialog emotion recognition (MDER) has recently received extensive research attention, which is also an essential branch of DL. The MDER aims to identify the emotional infor...