AIMC Topic: Neural Networks, Computer

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DyVGRNN: DYnamic mixture Variational Graph Recurrent Neural Networks.

Neural networks : the official journal of the International Neural Network Society
Although graph representation learning has been studied extensively in static graph settings, dynamic graphs are less investigated in this context. This paper proposes a novel integrated variational framework called DYnamic mixture Variational Graph ...

Denoising Tc-99m DMSA images using Denoising Convolutional Neural Network with comparison to a Block Matching Filter.

Nuclear medicine communications
INTRODUCTION: A DnCNN for image denoising trained with natural images is available in MATLAB. For Tc-99m DMSA images, any loss of clinical details during the denoising process will have serious consequences since denoised image is to be used for diag...

Recognizing Object by Components With Human Prior Knowledge Enhances Adversarial Robustness of Deep Neural Networks.

IEEE transactions on pattern analysis and machine intelligence
Adversarial attacks can easily fool object recognition systems based on deep neural networks (DNNs). Although many defense methods have been proposed in recent years, most of them can still be adaptively evaded. One reason for the weak adversarial ro...

Interpretable machine learning models for hospital readmission prediction: a two-step extracted regression tree approach.

BMC medical informatics and decision making
BACKGROUND: Advanced machine learning models have received wide attention in assisting medical decision making due to the greater accuracy they can achieve. However, their limited interpretability imposes barriers for practitioners to adopt them. Rec...

Predicting CircRNA-Disease Associations via Feature Convolution Learning With Heterogeneous Graph Attention Network.

IEEE journal of biomedical and health informatics
Exploring the relationship between circular RNA (circRNA) and disease is beneficial for revealing the mechanisms of disease pathogenesis. However, a blind search for all possible associations between circRNAs and diseases through biological experimen...

A Two-Branch Neural Network for Short-Axis PET Image Quality Enhancement.

IEEE journal of biomedical and health informatics
The axial field of view (FOV) is a key factor that affects the quality of PET images. Due to hardware FOV restrictions, conventional short-axis PET scanners with FOVs of 20 to 35 cm can acquire only low-quality PET (LQ-PET) images in fast scanning ti...

Microscopic Hyperspectral Image Classification Based on Fusion Transformer With Parallel CNN.

IEEE journal of biomedical and health informatics
Microscopic hyperspectral image (MHSI) has received considerable attention in the medical field. The wealthy spectral information provides potentially powerful identification ability when combining with advanced convolutional neural network (CNN). Ho...

Triplet-Net Classification of Contiguous Stem Cell Microscopy Images.

IEEE/ACM transactions on computational biology and bioinformatics
Cellular microscopy imaging is a common form of data acquisition for biological experimentation. Observation of gray-level morphological features allows for the inference of useful biological information such as cellular health and growth status. Cel...

A Comprehensive Survey of Deep Learning Techniques in Protein Function Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Protein function prediction is a major challenge in the field of bioinformatics which aims at predicting the functions performed by a known protein. Many protein data forms like protein sequences, protein structures, protein-protein interaction netwo...

Lite-SeqCNN: A Light-Weight Deep CNN Architecture for Protein Function Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
The short-and-long range interactions amongst amino-acids in a protein sequence are primarily responsible for the function performed by the protein. Recently convolutional neural network (CNN)s have produced promising results on sequential data inclu...