AIMC Topic: Deep Learning

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Classification of Pneumonia via a Hybrid ZFNet-Quantum Neural Network Using a Chest X-ray Dataset.

Current medical imaging
INTRODUCTION: Deep neural networks (DNNs) have made significant contributions to diagnosing pneumonia from chest X-ray imaging. However, certain aspects of diagnosis and planning can be further enhanced through the implementation of a quantum deep ne...

Multi-disease X-ray Image Classification of the Chest Based on Global and Local Fusion Adaptive Networks.

Current medical imaging
BACKGROUND: Chest X-ray image classification for multiple diseases is an important research direction in the field of computer vision and medical image processing. It aims to utilize advanced image processing techniques and deep learning algorithms t...

DNeuroMAT: A Deep-Learning-Based Neuron Morphology Analysis Toolbox.

Methods in molecular biology (Clifton, N.J.)
Digital reconstruction of neuronal structures from 3D neuron microscopy images is critical for the quantitative investigation of brain circuits and functions. Currently, neuron reconstructions are mainly obtained by manual or semiautomatic methods. H...

The impact of artificial intelligence in the diagnosis and management of acoustic neuroma: A systematic review.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Schwann cell sheaths are the source of benign, slowly expanding tumours known as acoustic neuromas (AN). The diagnostic and treatment approaches for AN must be patient-centered, taking into account unique factors and preferences.

Prediction of early-phase cytomegalovirus pneumonia in post-stem cell transplantation using a deep learning model.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Diagnostic challenges exist for CMV pneumonia in post-hematopoietic stem cell transplantation (post-HSCT) patients, despite early-phase radiographic changes.

Fine grained automatic left ventricle segmentation via ROI based Tri-Convolutional neural networks.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: The left ventricle segmentation (LVS) is crucial to the assessment of cardiac function. Globally, cardiovascular disease accounts for the majority of deaths, posing a significant health threat. In recent years, LVS has gained important at...

Multi-dimensional dense attention network for pixel-wise segmentation of optic disc in colour fundus images.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Segmentation of retinal fragments like blood vessels, Optic Disc (OD), and Optic Cup (OC) enables the early detection of different retinal pathologies like Diabetic Retinopathy (DR), Glaucoma, etc.

An effective deep learning-based approach for splice site identification in gene expression.

Science progress
A crucial stage in eukaryote gene expression involves mRNA splicing by a protein assembly known as the spliceosome. This step significantly contributes to generating and properly operating the ultimate gene product. Since non-coding introns disrupt e...

Alzheimer's Disease Prediction Using Fly-Optimized Densely Connected Convolution Neural Networks Based on MRI Images.

The journal of prevention of Alzheimer's disease
Alzheimer's is a degenerative brain cell disease that affects around 5.8 million people globally. The progressive neurodegenerative disease known as Alzheimer's Disease (AD), affects the frontal cortex, the part of the brain in charge of memory, lang...