AIMC Topic: Aged, 80 and over
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Generative models of MRI-derived neuroimaging features and associated dataset of 18,000 samples.
Scientific data
Dec 5, 2024
Availability of large and diverse medical datasets is often challenged by privacy and data sharing restrictions. Successful application of machine learning techniques for disease diagnosis, prognosis, and precision medicine, requires large amounts of...
DS-MS-TCN: Otago Exercises Recognition With a Dual-Scale Multi-Stage Temporal Convolutional Network.
IEEE journal of biomedical and health informatics
Dec 5, 2024
The Otago Exercise Program (OEP) represents a crucial rehabilitation initiative tailored for older adults, aimed at enhancing balance and strength. Despite previous efforts utilizing wearable sensors for OEP recognition, existing studies have exhibit...
Signed Curvature Graph Representation Learning of Brain Networks for Brain Age Estimation.
IEEE journal of biomedical and health informatics
Dec 5, 2024
Graph Neural Networks (GNNs) play a pivotal role in learning representations of brain networks for estimating brain age. However, the over-squashing impedes interactions between long-range nodes, hindering the ability of message-passing mechanism-bas...
Care home resident identification: A comparison of address matching methods with Natural Language Processing.
PloS one
Dec 5, 2024
BACKGROUND: Care home residents are a highly vulnerable group, but identifying care home residents in routine data is challenging. This study aimed to develop and validate Natural Language Processing (NLP) methods to identify care home residents from...
Predicting mental health treatment outcomes using latent growth mixture models and machine learning in a real-world clinical setting.
Journal of psychiatric research
Dec 4, 2024
Previous models of depression outcomes have been limited by symptom heterogeneity within populations. This study conducted a retrospective analysis using latent growth mixture models to identify heterogeneous trajectories within a clinical population...
Depression
Latent Class Analysis
Adolescent
Stress Disorders, Post-Traumatic
Treatment Outcome
Mental Health Services
Area Under Curve
ROC Curve
United States
Young Adult
Adult
Male
Middle Aged
Female
Reproducibility of Results
Aged
Aged, 80 and over
Humans
Machine Learning
Retrospective Studies
Outcome Assessment, Health Care
Veterans
Outpatients
Patient Health Questionnaire
Deep learning analysis of fMRI data for predicting Alzheimer's Disease: A focus on convolutional neural networks and model interpretability.
PloS one
Dec 4, 2024
The early detection of Alzheimer's Disease (AD) is thought to be important for effective intervention and management. Here, we explore deep learning methods for the early detection of AD. We consider both genetic risk factors and functional magnetic ...
A Machine learning classification framework using fused fractal property feature vectors for Alzheimer's disease diagnosis.
Brain research
Dec 3, 2024
Alzheimer's disease (AD) profoundly affects brain tissue and network structures. Analyzing the topological properties of these networks helps to understand the progression of the disease. Most studies focus on single-scale brain networks, but few add...
Assessing Locomotive Syndrome Through Instrumented Five-Time Sit-to-Stand Test and Machine Learning.
Sensors (Basel, Switzerland)
Dec 3, 2024
Locomotive syndrome (LS) refers to a condition where individuals face challenges in performing activities of daily living. Early detection of such deterioration is crucial to reduce the need for nursing care. The Geriatric Locomotive Function Scale (...
The use of cloud based machine learning to predict outcome in intracerebral haemorrhage without explicit programming expertise.
Neurosurgical review
Dec 3, 2024
Machine Learning (ML) techniques require novel computer programming skills along with clinical domain knowledge to produce a useful model. We demonstrate the use of a cloud-based ML tool that does not require any programming expertise to develop, val...
Prediction of Medication-Related Osteonecrosis of the Jaw in Patients Receiving Antiresorptive Therapy Using Machine Learning Models.
Journal of oral and maxillofacial surgery : official journal of the American Association of Oral and Maxillofacial Surgeons
Dec 2, 2024
BACKGROUND: Medication-related osteonecrosis of the jaw (MRONJ) is a serious complication associated with the use of antiresorptive agents, impacting patient quality of life and treatment outcomes. Predictive modeling may aid in a better understandin...
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