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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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Deep Learning to Improve Breast Cancer Detection on Screening Mammography.

The rapid development of deep learning, a family of machine learning techniques, has spurred much in...

Synchronization of memristive neural networks with leakage delay and parameters mismatch via event-triggered control.

In this paper, we investigate the synchronization problem on delayed memristive neural networks (MNN...

Do no harm: a roadmap for responsible machine learning for health care.

Interest in machine-learning applications within medicine has been growing, but few studies have pro...

rawMSA: End-to-end Deep Learning using raw Multiple Sequence Alignments.

In the last decades, huge efforts have been made in the bioinformatics community to develop machine ...

Indirect and direct training of spiking neural networks for end-to-end control of a lane-keeping vehicle.

Building spiking neural networks (SNNs) based on biological synaptic plasticities holds a promising ...

Integrated Robotic Mini Bioreactor Platform for Automated, Parallel Microbial Cultivation With Online Data Handling and Process Control.

During process development, the experimental search space is defined by the number of experiments th...

Time series classification with Echo Memory Networks.

Echo state networks (ESNs) are randomly connected recurrent neural networks (RNNs) that can be used ...

FusionAtt: Deep Fusional Attention Networks for Multi-Channel Biomedical Signals.

Recently, pervasive sensing technologies have been widely applied to comprehensive patient monitorin...

Simple Hyper-Heuristics Control the Neighbourhood Size of Randomised Local Search Optimally for LeadingOnes.

Selection hyper-heuristics (HHs) are randomised search methodologies which choose and execute heuris...

End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography.

With an estimated 160,000 deaths in 2018, lung cancer is the most common cause of cancer death in th...

Sample Fusion Network: An End-to-End Data Augmentation Network for Skeleton-Based Human Action Recognition.

Data augmentation is a widely used technique for enhancing the generalization ability of deep neural...

Sodium hydroxide-induced esophageal stricture via an endoscopic injection needle: a novel rabbit model of corrosive injury.

Benign strictures of the esophagus are commonly encountered in clinical practice and are difficult ...

Exploiting machine learning for end-to-end drug discovery and development.

A variety of machine learning methods such as naive Bayesian, support vector machines and more recen...

SPINDLE: End-to-end learning from EEG/EMG to extrapolate animal sleep scoring across experimental settings, labs and species.

Understanding sleep and its perturbation by environment, mutation, or medication remains a central p...

End-to-End Differentiable Learning of Protein Structure.

Predicting protein structure from sequence is a central challenge of biochemistry. Co-evolution meth...

Specific impact of past and new major cardiovascular events on acute kidney injury and end-stage renal disease risks in diabetes: a dynamic view.

BACKGROUND: Interconnections between major cardiovascular events (MCVEs) and renal events are recogn...

TSE-CNN: A Two-Stage End-to-End CNN for Human Activity Recognition.

Human activity recognition has been widely used in healthcare applications such as elderly monitorin...

Applications of an interaction, process, integration and intelligence (IPII) design approach for ergonomics solutions.

This paper first reviews current ergonomics design approaches in delivering digital solutions to ach...

Upper limb robot-assisted rehabilitation versus physical therapy on subacute stroke patients: A follow-up study.

This study aims to analyse the long-term effects (6 months follow-up) of upper limb Robot-assisted T...

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