Geriatrics

Deep Learning on SDF for Classifying Brain Biomarkers.

Biomarkers are one of the primary medical signs to facilitate the early detection of Alzheimer's disease. The small beta-amyloid (Aβ) peptide is an important indicator for the disease. However, current methods to detect Aβ pathology are either invasive (lumbar puncture) or quite costly and not widely available (amyloid PET). Thus a less invasive and cheaper approach is demanded. MRI which has been...

End-to-End Versatile Human Activity Recognition with Activity Image Transfer Learning.

Transfer learning is a common solution to address cross-domain identification problems in Human Activity Recognition (HAR). Most existing approaches typically perform cross-subject transferring while ignoring transfers between different sensors or body parts, which limits the application scope of these models. Only a few approaches have been made to design a versatile HAR approach (cross-subject, ...

Early Detection of Low Cognitive Scores from Dual-task Performance Data Using a Spatio-temporal Graph Convolutional Neural Network.

Detecting low cognitive scores at an early stage is important for delaying the progress of dementia. Investigations of early-stage detection have empl...

Leveraging Unsupervised Machine Learning to Discover Patterns in Linguistic Health Summaries for Eldercare.

The Center for Eldercare and Rehabilitation Technology, at University of Missouri, has researched the use of smart, unobtrusive sensors for older adul...

Federated Learning via Conditional Mutual Learning for Alzheimer's Disease Classification on T1w MRI.

Data-driven deep learning has been considered a promising method for building powerful models for medical data, which often requires a large amount of...

Data-Limited Deep Learning Methods for Mild Cognitive Impairment Classification in Alzheimer's Disease Patients.

Mild Cognitive Impairment (MCI) is the stage between the declining of normal brain function and the more serious decline of dementia. Alzheimer's dise...

Input Agnostic Deep Learning for Alzheimer's Disease Classification Using Multimodal MRI Images.

Alzheimer's disease (AD) is a progressive brain disorder that causes memory and functional impairments. The advances in machine learning and publicly ...

End-To-End Bioluminescence Tomography Reconstruction Based On Convolution Neural Network Scheme.

Bioluminescence tomography (BLT) has received a lot of attention as an important technique in bio-optical imaging. Compared with traditional methods, ...

DeepQSMSeg: A Deep Learning-based Sub-cortical Nucleus Segmentation Tool for Quantitative Susceptibility Mapping.

Deep brain nuclei are closely related to the pathogenesis of neurodegenerative diseases. Automatic segmentation for brain nuclei plays a significant r...

End-to-End Neural Network for Feature Extraction and Cancer Diagnosis of In Vivo Fluorescence Lifetime Images of Oral Lesions.

In contrast to previous studies that focused on classical machine learning algorithms and hand-crafted features, we present an end-to-end neural netwo...

Design of Novel End-effectors for Robot-assisted Swab Sampling to Combat Respiratory Infectious Diseases.

The COVID-19 outbreak has caused the mortality worldwide and the use of swab sampling is a common way of screening and diagnosis. To combat respirator...

Use of deep learning genomics to discriminate Alzheimer's disease and healthy controls.

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Because gene is an impo...

Autonomous Systems and Artificial Intelligence - Hype or Prerequisite for P5 Medicine?

For meeting the challenge of aging, multi-diseased societies, cost containment, workforce development and consumerism by improved care quality and pat...

Pan-Tissue Aging Clock Genes That Have Intimate Connections with the Immune System and Age-Related Disease.

In our recent transcriptomic meta-analysis, we used random forest machine learning to accurately predict age in human blood, bone, brain, heart, and r...

Inertial Tail Effects during Righting of Squirrels in Unexpected Falls: From Behavior to Robotics.

Arboreal mammals navigate a highly three dimensional and discontinuous habitat. Among arboreal mammals, squirrels demonstrate impressive agility. In a...

An end-to-end heterogeneous graph representation learning-based framework for drug-target interaction prediction.

Accurately identifying potential drug-target interactions (DTIs) is a key step in drug discovery. Although many related experimental studies have been...

Paediatric/young versus adult patients with long QT syndrome.

INTRODUCTION: Long QT syndrome (LQTS) is a less prevalent cardiac ion channelopathy than Brugada syndrome in Asia. The present study compared the outc...

Do you have COVID-19? An artificial intelligence-based screening tool for COVID-19 using acoustic parameters.

This study aimed to develop an artificial intelligence (AI)-based tool for screening COVID-19 patients based on the acoustic parameters of their voice...

Deep learning-based stereophonic acoustic echo suppression without decorrelation.

Traditional stereophonic acoustic echo cancellation algorithms need to estimate acoustic echo paths from stereo loudspeakers to a microphone, which of...

Evaluating resampling methods and structured features to improve fall incident report identification by the severity level.

OBJECTIVE: This study aims to improve the classification of the fall incident severity level by considering data imbalance issues and structured featu...