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Care of terminally ill / Palliative care

Latest AI and machine learning research in care of terminally ill / palliative care for healthcare professionals.

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Showing 484-504 of 6,160 articles
Deep learning techniques have significantly impacted protein structure prediction and protein design.

Protein structure prediction and design can be regarded as two inverse processes governed by the sam...

End-to-end novel visual categories learning via auxiliary self-supervision.

Semi-supervised learning has largely alleviated the strong demand for large amount of annotations in...

Computational reproductions of external force field adaption without assuming desired trajectories.

Optimal feedback control is an established framework that is used to characterize human movement. Ho...

A deep learning methodology for the automated detection of end-diastolic frames in intravascular ultrasound images.

Coronary luminal dimensions change during the cardiac cycle. However, contemporary volumetric intrav...

Feasibility of the use of deep learning classification of teat-end condition in Holstein cattle.

Infections with pathogenic bacteria entering the mammary gland through the teat canal are the most c...

Multi-Scale Context-Guided Deep Network for Automated Lesion Segmentation With Endoscopy Images of Gastrointestinal Tract.

Accurate lesion segmentation based on endoscopy images is a fundamental task for the automated diagn...

Large-Scale Modeling of Multispecies Acute Toxicity End Points Using Consensus of Multitask Deep Learning Methods.

Computational methods to predict molecular properties regarding safety and toxicology represent alte...

Design and Implementation of Fast Spoken Foul Language Recognition with Different End-to-End Deep Neural Network Architectures.

Given the excessive foul language identified in audio and video files and the detrimental consequenc...

An End-to-End Foreground-Aware Network for Person Re-Identification.

Person re-identification is a crucial task of identifying pedestrians of interest across multiple su...

4D deep image prior: dynamic PET image denoising using an unsupervised four-dimensional branch convolutional neural network.

Although convolutional neural networks (CNNs) demonstrate the superior performance in denoising posi...

DaNet: dose-aware network embedded with dose-level estimation for low-dose CT imaging.

Many deep learning (DL)-based image restoration methods for low-dose CT (LDCT) problems directly emp...

Fully end-to-end deep-learning-based diagnosis of pancreatic tumors.

Artificial intelligence can facilitate clinical decision making by considering massive amounts of me...

Developing a Qualification and Verification Strategy for Digital Tissue Image Analysis in Toxicological Pathology.

Digital tissue image analysis is a computational method for analyzing whole-slide images and extract...

Application of machine learning to improve dairy farm management: A systematic literature review.

In recent years, several researchers and practitioners applied machine learning algorithms in the da...

Deep multi-kernel auto-encoder network for clustering brain functional connectivity data.

In this study, we propose a deep-learning network model called the deep multi-kernel auto-encoder cl...

A dual-domain deep learning-based reconstruction method for fully 3D sparse data helical CT.

Helical CT has been widely used in clinical diagnosis. In this work, we focus on a new prototype of ...

LSTM-Based End-to-End Framework for Biomedical Event Extraction.

Biomedical event extraction plays an important role in the extraction of biological information from...

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