AIMC Topic: Adult

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Treadmill-Based Locomotor Training With Robotic Pelvic Assist and Visual Feedback: A Feasibility Study.

Journal of neurologic physical therapy : JNPT
BACKGROUND AND PURPOSE: Gait asymmetries are common after stroke, and often persist despite conventional rehabilitation. Robots provide training at a greater practice frequency than conventional approaches. However, prior studies of have found the tr...

Unsupervised machine learning and prognostic factors of survival in chronic lymphocytic leukemia.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Unsupervised machine learning approaches hold promise for large-scale clinical data. However, the heterogeneity of clinical data raises new methodological challenges in feature selection, choosing a distance metric that captures biological...

Using Supervised Learning Methods to Develop a List of Prescription Medications of Greatest Concern during Pregnancy.

Maternal and child health journal
INTRODUCTION: Women and healthcare providers lack adequate information on medication safety during pregnancy. While resources describing fetal risk are available, information is provided in multiple locations, often with subjective assessments of ava...

A Survey of Nurses' Need for Care Robots in Children's Hospitals: Combining Robot-Care, Game-Care, and Edu-Care.

Computers, informatics, nursing : CIN
The purpose of this study was to investigate nurses' need for care robots in children's hospitals and to help develop care robots that can be used by combining robot-care, game-care, and edu-care. This study employed a mixed-methods design; 198 nurse...

Decoding spectro-temporal representation for motor imagery recognition using ECoG-based brain-computer interfaces.

Journal of integrative neuroscience
One of the challenges in brain-computer interface systems is obtaining motor imagery recognition from brain activities. Brain-signal decoding robustness and system performance improvement during the motor imagery process are two of the essential issu...

Machine learning-based prediction of outcomes of the endoscopic endonasal approach in Cushing disease: is the future coming?

Neurosurgical focus
OBJECTIVE: Machine learning (ML) is an innovative method to analyze large and complex data sets. The aim of this study was to evaluate the use of ML to identify predictors of early postsurgical and long-term outcomes in patients treated for Cushing d...

Characterizing Individual Differences in a Dynamic Stabilization Task Using Machine Learning.

Aerospace medicine and human performance
: Being able to identify individual differences in skilled motor learning during disorienting conditions is important for spaceflight, military aviation, and rehabilitation.: Blindfolded subjects ( = 34) were strapped into a device that behaved like ...

Evaluation of admittance control as an alternative to passive arm supports to increase upper extremity function for individuals with Duchenne muscular dystrophy.

Muscle & nerve
The degree of upper extremity active range of motion provided by an admittance control robot compared with a commercially available passive arm support for individuals with DMD who have limited arm function was investigated in this study. The reachab...