AIMC Topic: Deep Learning

Clear Filters Showing 12301 to 12310 of 28423 articles

Coagulant dosage determination using deep learning-based graph attention multivariate time series forecasting model.

Water research
Determination of coagulant dosage in water treatment is a time-consuming process involving nonlinear data relationships and numerous factors. This study provides a deep learning approach to determine coagulant dosage and/or the settled water turbidit...

dtiRIM: A generalisable deep learning method for diffusion tensor imaging.

NeuroImage
Diffusion weighted MRI is an indispensable tool for routine patient screening and diagnostics of pathology. Recently, several deep learning methods have been proposed to quantify diffusion parameters, but poor generalisation to new data prevents broa...

Deep learning identified genetic variants for COVID-19-related mortality among 28,097 affected cases in UK Biobank.

Genetic epidemiology
Analysis of host genetic components provides insights into the susceptibility and response to viral infection such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). To reveal genetic de...

X-iPPGNet: A novel one stage deep learning architecture based on depthwise separable convolutions for video-based pulse rate estimation.

Computers in biology and medicine
Pulse rate (PR) is one of the most important markers for assessing a person's health. With the increasing demand for long-term health monitoring, much attention is being paid to contactless PR estimation using imaging photoplethysmography (iPPG). Thi...

Multiclass skin lesion localization and classification using deep learning based features fusion and selection framework for smart healthcare.

Neural networks : the official journal of the International Neural Network Society
BACKGROUND: The idea of smart healthcare has gradually gained attention as a result of the information technology industry's rapid development. Smart healthcare uses next-generation technologies i.e., artificial intelligence (AI) and Internet of Thin...

Implementing deep learning models for the classification of Echinococcus multilocularis infection in human liver tissue.

Parasites & vectors
BACKGROUND: The histological diagnosis of alveolar echinococcosis can be challenging. Decision support models based on deep learning (DL) are increasingly used to aid pathologists, but data on the histology of tissue-invasive parasitic infections are...

Validation of a deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from UK Biobank.

BMC medicine
BACKGROUND: Currently in the United Kingdom, cardiovascular disease (CVD) risk assessment is based on the QRISK3 score, in which 10% 10-year CVD risk indicates clinical intervention. However, this benchmark has limited efficacy in clinical practice a...

Deep learning-based attenuation map generation with simultaneously reconstructed PET activity and attenuation and low-dose application.

Physics in medicine and biology
. In PET/CT imaging, CT is used for positron emission tomography (PET) attenuation correction (AC). CT artifacts or misalignment between PET and CT can cause AC artifacts and quantification errors in PET. Simultaneous reconstruction (MLAA) of PET act...

Deep Learning-Based Dose Prediction for Automated, Individualized Quality Assurance of Head and Neck Radiation Therapy Plans.

Practical radiation oncology
PURPOSE: This study aimed to use deep learning-based dose prediction to assess head and neck (HN) plan quality and identify suboptimal plans.