Care of terminally ill / Palliative care

Federated Learning for Privacy Preservation in Smart Healthcare Systems: A Comprehensive Survey.

Recent advances in electronic devices and communication infrastructure have revolutionized the traditional healthcare system into a smart healthcare system by using internet of medical things (IoMT) devices. However, due to the centralized training approach of artificial intelligence (AI), mobile and wearable IoMT devices raise privacy issues concerning the information communicated between hospita...

Informing clinical assessment by contextualizing post-hoc explanations of risk prediction models in type-2 diabetes.

Medical experts may use Artificial Intelligence (AI) systems with greater trust if these are supported by 'contextual explanations' that let the practitioner connect system inferences to their context of use. However, their importance in improving model usage and understanding has not been extensively studied. Hence, we consider a comorbidity risk prediction scenario and focus on contexts regardin...

Industrializing AI/ML during the end-to-end drug discovery process.

Drug discovery aims to select proper targets and drug candidates to address unmet clinical needs. The end-to-end drug discovery process includes all s...

Using self-supervised feature learning to improve the use of pulse oximeter signals to predict paediatric hospitalization.

: The success of many machine learning applications depends on knowledge about the relationship between the input data and the task of interest (outpu...

PRA-Net: Part-and-Relation Attention Network for depression recognition from facial expression.

Artificial intelligence methods are widely applied to depression recognition and provide an objective solution. Many effective automated methods for d...

ResSKNet-SSDP: Effective and Light End-To-End Architecture for Speaker Recognition.

In speaker recognition tasks, convolutional neural network (CNN)-based approaches have shown significant success. Modeling the long-term contexts and ...

Deep Learning Analysis of Chest Radiographs to Triage Patients with Acute Chest Pain Syndrome.

Background Patients presenting to the emergency department (ED) with acute chest pain (ACP) syndrome undergo additional testing to exclude acute coron...

An end-end deep learning framework for lesion segmentation on multi-contrast MR images-an exploratory study in a rat model of traumatic brain injury.

Traumatic brain injury (TBI) engenders traumatic necrosis and penumbra-areas of secondary neural injury which are crucial targets for therapeutic inte...

Towards Single Camera Human 3D-Kinematics.

Markerless estimation of 3D Kinematics has the great potential to clinically diagnose and monitor movement disorders without referrals to expensive mo...

Minimizing the effect of white matter lesions on deep learning based tissue segmentation for brain volumetry.

Automated methods for segmentation-based brain volumetry may be confounded by the presence of white matter (WM) lesions, which introduce abnormal inte...

End-to-End One-Shot Path-Planning Algorithm for an Autonomous Vehicle Based on a Convolutional Neural Network Considering Traversability Cost.

Path planning plays an important role in navigation and motion planning for robotics and automated driving applications. Most existing methods use ite...

Artificial intelligence for localization of the acute ischemic stroke by non-contrast computed tomography.

A non-contrast cranial computer tomography (ncCT) is often employed for the diagnosis of the early stage of the ischemic stroke. However, the number o...

End-to-End Hierarchical Reinforcement Learning With Integrated Subgoal Discovery.

Hierarchical reinforcement learning (HRL) is a promising approach to perform long-horizon goal-reaching tasks by decomposing the goals into subgoals. ...

End-to-End Protein Normal Mode Frequency Predictions Using Language and Graph Models and Application to Sonification.

The prediction of mechanical and dynamical properties of proteins is an important frontier, especially given the greater availability of proteins stru...

Adaptive Prescribed Performance Control of A Flexible-Joint Robotic Manipulator With Dynamic Uncertainties.

An adaptive fuzzy control strategy is proposed for a single-link flexible-joint robotic manipulator (SFRM) with prescribed performance, in which the u...

A Novel Multiple-View Adversarial Learning Network for Unsupervised Domain Adaptation Action Recognition.

Abstract-domain adaptation action recognition is a hot research topic in machine learning and some effective approaches have been proposed. However, s...

Adaptive-Constrained Impedance Control for Human-Robot Co-Transportation.

Human-robot co-transportation allows for a human and a robot to perform an object transportation task cooperatively on a shared environment. This rang...

ToxMVA: An end-to-end multi-view deep autoencoder method for protein toxicity prediction.

Effectively predicting protein toxicity plays an essential step in the early stage of protein-based drug discovery, which is of great help to speed up...

UNav: An Infrastructure-Independent Vision-Based Navigation System for People with Blindness and Low Vision.

Vision-based localization approaches now underpin newly emerging navigation pipelines for myriad use cases, from robotics to assistive technologies. C...

Protein structure prediction in the deep learning era.

Significant advances have been achieved in protein structure prediction, especially with the recent development of the AlphaFold2 and the RoseTTAFold ...