Geriatrics

Deep STI: Deep Stochastic Time-series Imputation on Electronic Health Records.

Electronic Health Records (EHRs) are a cornerstone of modern healthcare analytics, offering rich datasets for various disease analyses through advanced deep learning algorithms. However, the pervasive issue of missing values in EHRs significantly hampers the development and performance of these models. Addressing this challenge is crucial for enhancing clinical decision-making and patient care. Ex...

Brain Age Analysis and Dementia Classification using Convolutional Neural Networks trained on Diffusion MRI: Tests in Indian and North American Cohorts.

Deep learning models based on convolutional neural networks (CNNs) have been used to classify Alzheimer's disease or infer dementia severity from T1-weighted brain MRI scans. Here, we examine the value of adding diffusion-weighted MRI (dMRI) as an input to these models. Much research in this area focuses on specific datasets such as the Alzheimer's Disease Neuroimaging Initiative (ADNI), which ass...

Dual Attention Graph Convolutional Network Fusing Imaging and Genetic Data for Early Alzheimer's Disease Diagnosis.

Alzheimer's Disease (AD) poses a significant global neurodegenerative challenge, underscoring the urgency of early clinical intervention. Our paper pr...

Identifying Prediabetes in Canadian Populations Using Machine Learning.

Prediabetes is a critical health condition characterized by elevated blood glucose levels that fall below the threshold for Type 2 diabetes (T2D) diag...

Vascular Age Evaluation Enhanced using Recurrence Plot Analysis and Convolutional Neural Networks: An in-Silico Study.

Aging contributes as a major nonreversible risk factor for cardiovascular disease. This underscores the emergence of Vascular Age (VA) as a promising ...

Novel Alzheimer's Disease Stating Based on Comorbidities-Informed Graph Neural Networks.

Alzheimer's Disease (AD), the most prevalent form of dementia, requires early prediction for timely intervention. Leveraging data from the Alzheimer's...

3D Multi-feature fusion convolutional network for Alzheimer's disease diagnosis.

The cognitive decline caused by Alzheimer's disease (AD) is closely related to the structural changes in the hippocampus captured by structural magnet...

Artificial Intelligence Based Hierarchical Classification of Frontotemporal Dementia.

Frontotemporal dementia (FTD) is a typical kind of presenile dementia with three main subtypes: behavioral-variant FTD (bvFTD), non-fluent variant pri...

Multi-class Prediction of Cognitively Normal / Mild Cognitive Impairment / Alzheimer's Disease Status in Dementia Based on Convolutional Neural Networks with Attention Mechanism.

Alzheimer's disease (AD) is a neurodegenerative disease with insidious onset and progressive development. AD is a health issue that is attracting atte...

Video-based Clinical Gait Analysis in Parkinson's Disease: A Novel Approach Using Frontal Plane Videos and Machine Learning.

Gait can be significantly impaired by neurological conditions such as Parkinson's disease (PD). Gait impairments can be quantified by using instrument...

Machine Learning Approach for Music Familiarity Classification with Single-Channel EEG.

Recognition of familiar music on brainwaves through machine learning (ML) can be instrumental in innovative therapeutic devices that improve memory an...

Computer vision-inspired contrastive learning for self-supervised anomaly detection in sensor-based remote healthcare monitoring.

Sensor-based remote healthcare monitoring is a promising approach for timely detection of adverse health events such as falls or infections in people ...

Cross-Modality Translation with Generative Adversarial Networks to Unveil Alzheimer's Disease Biomarkers.

Generative approaches for cross-modality transformation have recently gained significant attention in neuroimaging. While most previous work has focus...

Walking Speed and Uncertainty Estimation Using Mixture Density Networks for Dynamic Ambulatory Environments.

Walking speed, often considered a representative indicator of activity levels, becomes notably reduced as muscle strength and cardiovascular function ...

Dementia Detection by In-Text Pause Encoding.

In dementia, particularly Alzheimer's Disease (AD), communication challenges are evident, especially in vocabulary and pragmatic aspects. Affected ind...

Deep Learning Analysis of Retinal Structures and Risk Factors of Alzheimer's Disease.

The importance of early Alzheimer's Disease screening is becoming more apparent, given the fact that there is no way to revert the patient's status af...

Influence of Personality Traits on Plagiarism Through Collusion in Programming Assignments

Educating students about academic integrity expectations has been suggested as one of the ways to reduce malpractice in take-home programming assign...

ACE: A Generative Cross-Modal Retrieval Framework with Coarse-To-Fine Semantic Modeling

Generative retrieval, which has demonstrated effectiveness in text-to-text retrieval, utilizes a sequence-to-sequence model to directly generate can...

Artificial intelligence for automatic detection of basal cell carcinoma from frozen tissue tangential biopsies.

Evaluation of basal cell carcinoma (BCC) involves tangential biopsies of a suspicious lesion that is sent for frozen sections and evaluated by a Mohs ...

[An ensemble model for assisting early Alzheimer's disease diagnosis based on structural magnetic resonance imaging with dual-time-point fusion].

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder. Due to the subtlety of symptoms in the early stages of AD, rapid and accurate cl...