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Outcome Assessment, Health Care

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Safety and immediate effects of Hybrid Assistive Limb in children with cerebral palsy: A pilot study.

Brain & development
PURPOSE: Early intervention is effective for developing motor ability and preventing contractures and deformities in patients with cerebral palsy (CP). Gait training using the newly developed Hybrid Assistive Limb (HAL) shows promise as an interventi...

The hidden information in patient-reported outcomes and clinician-assessed outcomes: multiple sclerosis as a proof of concept of a machine learning approach.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Machine learning (ML) applied to patient-reported (PROs) and clinical-assessed outcomes (CAOs) could favour a more predictive and personalized medicine. Our aim was to confirm the important role of applying ML to PROs and CAOs of people with relapsin...

Review of outcome measures in PARO robot intervention studies for dementia care.

Geriatric nursing (New York, N.Y.)
The aim of this study was to describe interventions for PARO, as well as the outcomes evaluated and found following use of PARO, and to identify outcome measures in PARO intervention studies for older adults with dementia. Multiple databases (Web of ...

Analysis of substance use and its outcomes by machine learning I. Childhood evaluation of liability to substance use disorder.

Drug and alcohol dependence
BACKGROUND: Substance use disorder (SUD) exacts enormous societal costs in the United States, and it is important to detect high-risk youths for prevention. Machine learning (ML) is the method to find patterns and make prediction from data. We hypoth...

Applying density-based outlier identifications using multiple datasets for validation of stroke clinical outcomes.

International journal of medical informatics
INTRODUCTION: Clinicians commonly use the modified Rankin Scale (mRS) and the Barthel Index (BI) to measure clinical outcome after stroke. These are potential targets in machine learning models for stroke outcome prediction. Therefore, the quality of...

Can machine learning improve patient selection for cardiac resynchronization therapy?

PloS one
RATIONALE: Multiple clinical trials support the effectiveness of cardiac resynchronization therapy (CRT); however, optimal patient selection remains challenging due to substantial treatment heterogeneity among patients who meet the clinical practice ...

Machine Learning in Epidemiology and Health Outcomes Research.

Annual review of public health
Machine learning approaches to modeling of epidemiologic data are becoming increasingly more prevalent in the literature. These methods have the potential to improve our understanding of health and opportunities for intervention, far beyond our past ...

Robot-assisted gait training for balance and lower extremity function in patients with infratentorial stroke: a single-blinded randomized controlled trial.

Journal of neuroengineering and rehabilitation
BACKGROUND: Balance impairments are common in patients with infratentorial stroke. Although robot-assisted gait training (RAGT) exerts positive effects on balance among patients with stroke, it remains unclear whether such training is superior to con...