AIMC Topic: Neural Networks, Computer

Clear Filters Showing 17381 to 17390 of 31376 articles

Analysing wideband absorbance immittance in normal and ears with otitis media with effusion using machine learning.

Scientific reports
Wideband Absorbance Immittance (WAI) has been available for more than a decade, however its clinical use still faces the challenges of limited understanding and poor interpretation of WAI results. This study aimed to develop Machine Learning (ML) too...

MichiGAN: sampling from disentangled representations of single-cell data using generative adversarial networks.

Genome biology
Deep generative models such as variational autoencoders (VAEs) and generative adversarial networks (GANs) generate and manipulate high-dimensional images. We systematically assess the complementary strengths and weaknesses of these models on single-c...

Kinematics approach with neural networks for early detection of sepsis (KANNEDS).

BMC medical informatics and decision making
BACKGROUND: Sepsis is a severe illness that affects millions of people worldwide, and its early detection is critical for effective treatment outcomes. In recent years, researchers have used models to classify positive patients or identify the probab...

Segmenting lung lesions of COVID-19 from CT images via pyramid pooling improved Unet.

Biomedical physics & engineering express
Segmenting lesion regions of Coronavirus Disease 2019 (COVID-19) from computed tomography (CT) images is a challenge owing to COVID-19 lesions characterized by high variation, low contrast between infection lesions and around normal tissues, and blur...

Pancreas segmentation with probabilistic map guided bi-directional recurrent UNet.

Physics in medicine and biology
Pancreas segmentation in medical imaging is of great significance for clinical pancreas diagnostics and treatment. However, the large population variations in the pancreas shape and volume cause enormous segmentation difficulties, even for state-of-t...

A COVID-19 Pandemic Artificial Intelligence-Based System With Deep Learning Forecasting and Automatic Statistical Data Acquisition: Development and Implementation Study.

Journal of medical Internet research
BACKGROUND: More than 79.2 million confirmed COVID-19 cases and 1.7 million deaths were caused by SARS-CoV-2; the disease was named COVID-19 by the World Health Organization. Control of the COVID-19 epidemic has become a crucial issue around the glob...

High-frequency conductivity at Larmor-frequency in human brain using moving local window multilayer perceptron neural network.

PloS one
Magnetic resonance electrical properties tomography (MREPT) aims to visualize the internal high-frequency conductivity distribution at Larmor frequency using the B1 transceive phase data. From the magnetic field perturbation by the electrical field a...

Machine learning in medicine: what clinicians should know.

Singapore medical journal
With the advent of artificial intelligence (AI), machines are increasingly being used to complete complicated tasks, yielding remarkable results. Machine learning (ML) is the most relevant subset of AI in medicine, which will soon become an integral ...

Automatic cervical lymphadenopathy segmentation from CT data using deep learning.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to develop a fast and automatic algorithm to detect and segment lymphadenopathy from head and neck computed tomography (CT) examination.

Feasibility of a generalized convolutional neural network for automated identification of vertebral compression fractures: The Manitoba Bone Mineral Density Registry.

Bone
BACKGROUND: Vertebral fracture assessment (VFA) images are acquired in dual-energy (DE) or single-energy (SE) scan modes. Automated identification of vertebral compression fractures, from VFA images acquired using GE Healthcare scanners in DE mode, h...