Geriatrics

Real Time Hand Movement Trajectory Tracking for Enhancing Dementia Screening in Ageing Deaf Signers of British Sign Language.

Real time hand movement trajectory tracking based on machine learning approaches may assist the earl...

Toward an interpretable Alzheimer's disease diagnostic model with regional abnormality representation via deep learning.

In this paper, we propose a novel method for magnetic resonance imaging based Alzheimer's disease (A...

Prognostic networks for unraveling the biological mechanisms of Sarcopenia.

Sarcopenia is an age-related multifactorial process that involved several biological mechanisms, who...

Cognitive prostheses for goal achievement.

Procrastination takes a considerable toll on people's lives, the economy and society at large. Procr...

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...

Deep Learning Enhancing Kinome-Wide Polypharmacology Profiling: Model Construction and Experiment Validation.

The kinome-wide virtual profiling of small molecules with high-dimensional structure-activity data i...

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 ...

Network latency and long-distance robotic telestenting: Exploring the potential impact of network delays on telestenting performance.

OBJECTIVE: This study evaluated the impact of network latency on telestenting performance.

Toward a Better Estimation of Functional Brain Network for Mild Cognitive Impairment Identification: A Transfer Learning View.

Mild cognitive impairment (MCI) is an intermediate stage of brain cognitive decline, associated with...

Feasibility of robotic telestenting over long geographic distances: a pre-clinical ex vivo and in vivo study.

Automatic extraction and assessment of lifestyle exposures for Alzheimer's disease using natural language processing.

INTRODUCTION: Previous biomedical studies identified many lifestyle exposures that could possibly re...

Trends in Alzheimer's Disease Research Based upon Machine Learning Analysis of PubMed Abstracts.

About 29.8 million people worldwide had been diagnosed with Alzheimer's disease (AD) in 2015, and th...

Artificial Intelligence for Drug Toxicity and Safety.

Interventional pharmacology is one of medicine's most potent weapons against disease. These drugs, h...

Characterizing Alzheimer's Disease With Image and Genetic Biomarkers Using Supervised Topic Models.

Neuroimaging and genetic biomarkers have been widely studied from discriminative perspectives toward...

Telepresence robots: Encouraging interactive communication between family carers and people with dementia.

OBJECTIVE: The aim of the study was to explore the feasibility of using telepresence robots to encou...

Accurate and interpretable evaluation of surgical skills from kinematic data using fully convolutional neural networks.

PURPOSE: Manual feedback from senior surgeons observing less experienced trainees is a laborious tas...

[Machine learning for predictive analyses in health: an example of an application to predict death in the elderly in São Paulo, Brazil].

This study aims to present the stages related to the use of machine learning algorithms for predicti...

Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department.

BACKGROUND: Falls among older adults are both a common reason for presentation to the emergency depa...

Deep Learning of Static and Dynamic Brain Functional Networks for Early MCI Detection.

While convolutional neural network (CNN) has been demonstrating powerful ability to learn hierarchic...

Machine Learning for Automatic Paraspinous Muscle Area and Attenuation Measures on Low-Dose Chest CT Scans.

RATIONALE AND OBJECTIVES: To develop and evaluate an automated machine learning (ML) algorithm for s...

Using deep Siamese neural networks for detection of brain asymmetries associated with Alzheimer's Disease and Mild Cognitive Impairment.

In recent studies, neuroanatomical volume and shape asymmetries have been seen during the course of ...