Current functional assessment instruments in stroke rehabilitation are often setting-specific and lack precision, breadth, and/or feasibility. Computer adaptive testing (CAT) offers a promising potential solution by providing a quick, yet precise, measure of function that can be used across a broad range of patient abilities and in multiple settings. CAT technology yields a precise score by selecting very few relevant items from a large and diverse item pool based on each individual's responses. We demonstrate the potential usefulness of a CAT assessment model with a cross-sectional sample of persons with stroke from multiple rehabilitation settings.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1310/CUAN-ML5R-FWHD-0EQL | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
A 3D decoupling Alzheimer's disease prediction network based on structural MRI.
Health Inf Sci Syst
December 2025
School of Mathematics and Computing, University of Southern Queensland, 487-535 West Street, Toowoomba, QLD 4350 Australia.
Purpose: This paper aims to develop a three-dimensional (3D) Alzheimer's disease (AD) prediction method, thereby bettering current predictive methods, which struggle to fully harness the potential of structural magnetic resonance imaging (sMRI) data.
Methods: Traditional convolutional neural networks encounter pressing difficulties in accurately focusing on the AD lesion structure. To address this issue, a 3D decoupling, self-attention network for AD prediction is proposed.
The game of language learning and rewiring biocognitive receptors.
MethodsX
June 2025
School of Computer Science and Engineering, Vellore Institute of Technology, Vandalur - Kelambakkam Road, Chennai, 600 127 Tamil Nadu, India.
This study introduces a framework that integrates AI-driven Game-Based Language Teaching (GBLT) with advanced neuroscience to transform language education for visually impaired learners. Built on the principles of neuroplasticity and epigenetics, the approach leverages educational psychology with the help of adaptive AI to deliver personalized, gamified learning experiences that reshape neural pathways, improve memory retention, and strengthen emotional resilience. By fostering low-stress, immersive environments, it triggers positive epigenetic changes, enhancing long-term cognitive flexibility.
View Article and Find Full Text PDFRight ventricular heart failure (RV HF) is the leading cause of death in pulmonary arterial hypertension (PAH). Relevance of the low-risk status assessment using available diagnostic tools requires a reliable confirmation. The study aimed to evaluate right ventricular perfusion and glucose metabolism using positron emission tomography (PET)/computed tomography (CT) with [13N]-ammonia and [18F]-fluorodeoxyglucose ([18F]-FDG) in 30 IPAH patients (33.
View Article and Find Full Text PDFReal-time mechanism-based interventions for daily alcohol challenges: Protocol for ecological momentary assessment and intervention.
Digit Health
January 2025
Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany.
Background: Advancing evidence-based, tailored interventions for substance use disorders (SUDs) requires understanding temporal directionality while upholding ecological validity. Previous studies identified loneliness and craving as pivotal factors associated with alcohol consumption, yet the precise directionality of these relationships remains ambiguous.
Objective: This study aims to establish a smartphone-based real-life intervention platform that integrates momentary assessment and intervention into everyday life.
Next-gen agriculture: integrating AI and XAI for precision crop yield predictions.
Front Plant Sci
January 2025
Department of Computer Science and Engineering, Indian Institute of Information Technology Design and Manufacturing (III TDM), Kurnool, Andhrapradesh, India.
Climate change poses significant challenges to global food security by altering precipitation patterns and increasing the frequency of extreme weather events such as droughts, heatwaves, and floods. These phenomena directly affect agricultural productivity, leading to lower crop yields and economic losses for farmers. This study leverages Artificial Intelligence (AI) and Explainable Artificial Intelligence (XAI) techniques to predict crop yields and assess the impacts of climate change on agriculture, providing a novel approach to understanding complex interactions between climatic and agronomic factors.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!