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Disability Evaluation

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Decision Tree Algorithm Identifies Stroke Patients Likely Discharge Home After Rehabilitation Using Functional and Environmental Predictors.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association 33545520
BACKGROUND AND PURPOSE: The importance of environmental factors for stroke patients to achieve home discharge was not scientifically proven. There are limited studies on the application of the decision tree algorithm with various functional and envir...
Aged Aged, 80 and over Databases, Factual Decision Support Techniques Decision Trees Disability Evaluation Environment Female Functional Status Humans Machine Learning Male Middle Aged Motor Activity Patient Discharge Predictive Value of Tests Recovery of Function Stroke Stroke Rehabilitation Time Factors Treatment Outcome
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Exploring Associations of Preoperative Physical Performance With Postoperative Outcomes After Lumbar Spinal Fusion: A Machine Learning Approach.

Archives of physical medicine and rehabilitation 33711278
OBJECTIVE: To explore the association between preoperative physical performance with short- and long-term postoperative outcomes in patients undergoing lumbar spinal fusion (LSF).
Aged Cohort Studies Disability Evaluation Female Humans Length of Stay Lumbar Vertebrae Machine Learning Male Middle Aged Pain, Postoperative Patient Reported Outcome Measures Physical Functional Performance Postoperative Period Predictive Value of Tests Preoperative Period Recovery of Function Retrospective Studies Risk Factors Spinal Fusion
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Effects of a Soft Robotic Hand for Hand Rehabilitation in Chronic Stroke Survivors.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association 33895427
OBJECTIVES: Soft robotic hands are proposed for stroke rehabilitation in terms of their high compliance and low inherent stiffness. We investigated the clinical efficacy of a soft robotic hand that could actively flex and extend the fingers in chroni...
Adult Aged Biomechanical Phenomena Disability Evaluation Electromyography Equipment Design Exoskeleton Device Female Functional Status Hand Hand Strength Humans Male Middle Aged Motor Activity Recovery of Function Robotics Stroke Stroke Rehabilitation Time Factors Treatment Outcome
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Machine Learning Algorithm Identifies the Importance of Environmental Factors for Hospital Discharge to Home of Stroke Patients using Wheelchair after Discharge.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association 34029887
BACKGROUND AND PURPOSE: Physical environmental factors are generally likely to become barriers for discharge to home of wheelchair users, compared with non-wheelchair users. However, the importance of environmental factors has not been investigated a...
Activities of Daily Living Aged Aged, 80 and over Clinical Decision-Making Databases, Factual Decision Support Techniques Disability Evaluation Environment Design Female Housing Humans Machine Learning Male Mobility Limitation Patient Discharge Self-Help Devices Stroke Stroke Rehabilitation Treatment Outcome Wheelchairs
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Large Vessel Occlusion Prediction in the Emergency Department with National Institutes of Health Stroke Scale Components: A Machine Learning Approach.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association 34403842
OBJECTIVE: To determine the feasibility of using a machine learning algorithm to screen for large vessel occlusions (LVO) in the Emergency Department (ED).
Cerebrovascular Disorders Disability Evaluation Emergency Service, Hospital Feasibility Studies Female Functional Status Humans Machine Learning Male Middle Aged Predictive Value of Tests Prognosis Retrospective Studies
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Evaluation of Disability Progression in Multiple Sclerosis via Magnetic-Resonance-Based Deep Learning Techniques.

International journal of molecular sciences 36142563
Short-term disability progression was predicted from a baseline evaluation in patients with multiple sclerosis (MS) using their three-dimensional T1-weighted (3DT1) magnetic resonance images (MRI). One-hundred-and-eighty-one subjects diagnosed with M...
Brain Deep Learning Disability Evaluation Disease Progression Humans Magnetic Resonance Imaging Multiple Sclerosis
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Development of an ontology to characterize mental functioning.

Disability and rehabilitation 37702040
PURPOSE OF THE ARTICLE: This article describes a conceptual and methodological approach to integrating functional information into an ontology to categorize mental functioning, which to date is an under-developed area of classification, and supports ...
Disability Evaluation Humans International Classification of Functioning, Disability and Health Natural Language Processing Persons with Disabilities United States United States Social Security Administration
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Effect of Robotic Rehabilitation on Hand Functions and Quality of Life in Children With Cerebral Palsy: A Prospective Randomized Controlled Study.

American journal of physical medicine & rehabilitation 38320248
OBJECTIVE: This study aimed to examine the impact of robotic hand rehabilitation on hand function and quality of life in children with cerebral palsy.
Adolescent Cerebral Palsy Child Disability Evaluation Female Hand Hand Strength Humans Male Prospective Studies Quality of Life Robotics Treatment Outcome
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Interpretable and Intuitive Machine Learning Approaches for Predicting Disability Progression in Relapsing-Remitting Multiple Sclerosis Based on Clinical and Gray Matter Atrophy Indicators.

Academic radiology 38429188
RATIONALE AND OBJECTIVES: To investigate whether clinical and gray matter (GM) atrophy indicators can predict disability in relapsing-remitting multiple sclerosis (RRMS) and to enhance the interpretability and intuitiveness of a predictive machine le...
Adult Atrophy Disability Evaluation Disease Progression Female Gray Matter Humans Machine Learning Magnetic Resonance Imaging Male Middle Aged Multiple Sclerosis, Relapsing-Remitting Retrospective Studies
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Developing an Accumulative Assessment System of Upper Extremity Motor Function in Patients With Stroke Using Deep Learning.

Physical therapy 38531775
OBJECTIVE: The Fugl-Meyer assessment for upper extremity (FMA-UE) is a measure for assessing upper extremity motor function in patients with stroke. However, the considerable administration time of the assessment decreases its feasibility. This study...
Aged Deep Learning Disability Evaluation Female Humans Male Middle Aged Psychometrics Recovery of Function Reproducibility of Results Stroke Stroke Rehabilitation Upper Extremity
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