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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 316-336 of 6,157 articles
Adaptive Biological Neural Network Control and Virtual Realization for Engineering Manipulator.

By analyzing the feasibility of the digital twin technology in the assembly of construction machiner...

Evaluating molecular representations in machine learning models for drug response prediction and interpretability.

Machine learning (ML) is increasingly being used to guide drug discovery processes. When applying ML...

End-to-End Point Cloud Completion Network with Attention Mechanism.

We propose a conceptually simple, general framework and end-to-end approach to point cloud completio...

Deep learning-based image deconstruction method with maintained saliency.

Visual properties that primarily attract bottom-up attention are collectively referred to as salienc...

LTPConstraint: a transfer learning based end-to-end method for RNA secondary structure prediction.

BACKGROUND: RNA secondary structure is very important for deciphering cell's activity and disease oc...

A Machine Learning Perspective on fNIRS Signal Quality Control Approaches.

Despite a rise in the use of functional Near Infra-Red Spectroscopy (fNIRS) to study neural systems,...

Feedback Pinning Control of Successive Lag Synchronization on a Dynamical Network.

In nature and human society, successive lag synchronization (SLS) is an important synchronization ph...

NanoNet: Rapid and accurate end-to-end nanobody modeling by deep learning.

Antibodies are a rapidly growing class of therapeutics. Recently, single domain camelid VHH antibodi...

Toward Robust, Adaptiveand Reliable Upper-Limb Motion Estimation Using Machine Learning and Deep Learning-A Survey in Myoelectric Control.

To develop multi-functionalhuman-machine interfaces that can help disabled people reconstruct lost f...

An End-to-End Human Abnormal Behavior Recognition Framework for Crowds With Mentally Disordered Individuals.

Abnormal or violent behavior by people with mental disorders is common. When individuals with mental...

An Effective Deep Learning Model for Health Monitoring and Detection of COVID-19 Infected Patients: An End-to-End Solution.

The COVID-19 infection is the greatest danger to humankind right now because of the devastation it c...

Application of Deep Learning Workflow for Autonomous Grain Size Analysis.

Traditional grain size determination in materials characterization involves microscopy images and a ...

Permutation Invariant Graph-to-Sequence Model for Template-Free Retrosynthesis and Reaction Prediction.

Synthesis planning and reaction outcome prediction are two fundamental problems in computer-aided or...

Face mediated human-robot interaction for remote medical examination.

Realtime visual feedback from consequences of actions is useful for future safety-critical human-rob...

End-to-end deep learning framework for printed circuit board manufacturing defect classification.

We report a complete deep-learning framework using a single-step object detection model in order to ...

Unified End-to-End YOLOv5-HR-TCM Framework for Automatic 2D/3D Human Pose Estimation for Real-Time Applications.

Three-dimensional human pose estimation is widely applied in sports, robotics, and healthcare. In th...

Human Grasp Mechanism Understanding, Human-Inspired Grasp Control and Robotic Grasping Planning for Agricultural Robots.

As the end execution tool of agricultural robots, the manipulator directly determines whether the gr...

Improvement of Speech Recognition Technology in Piano Music Scene Based on Deep Learning of Internet of Things.

The main goal of speech recognition technology is to use computers to convert human analog speech si...

Feasibility study of three-material decomposition in dual-energy cone-beam CT imaging with deep learning.

In this work, a dedicated end-to-end deep convolutional neural network, named as Triple-CBCT, is pro...

A novel end-to-end deep learning solution for coronary artery segmentation from CCTA.

PURPOSE: Coronary computed tomographic angiography (CCTA) plays a vital role in the diagnosis of car...

Application of deep learning methods: From molecular modelling to patient classification.

We are now well into the information driven age with complex, heterogeneous, datasets in the biologi...

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