AIMC Topic: Adult

Clear Filters Showing 10011 to 10020 of 15606 articles

Robotic body weight support enables safe stair negotiation in compliance with basic locomotor principles.

Journal of neuroengineering and rehabilitation
BACKGROUND: After a neurological injury, mobility focused rehabilitation programs intensively train walking on treadmills or overground. However, after discharge, quite a few patients are not able to independently negotiate stairs, a real-world task ...

Detecting prolonged sitting bouts with the ActiGraph GT3X.

Scandinavian journal of medicine & science in sports
The ActiGraph has a high ability to measure physical activity; however, it lacks an accurate posture classification to measure sedentary behavior. The aim of the present study was to develop an ActiGraph (waist-worn, 30 Hz) posture classification to ...

Prediction of lower-grade glioma molecular subtypes using deep learning.

Journal of neuro-oncology
INTRODUCTION: It is useful to know the molecular subtype of lower-grade gliomas (LGG) when deciding on a treatment strategy. This study aims to diagnose this preoperatively.

Gender and active travel: a qualitative data synthesis informed by machine learning.

The international journal of behavioral nutrition and physical activity
BACKGROUND: Innovative approaches are required to move beyond individual approaches to behaviour change and develop more appropriate insights for the complex challenge of increasing population levels of activity. Recent research has drawn on social p...

Ultrasonic liver steatosis quantification by a learning-based acoustic model from a novel shear wave sequence.

Biomedical engineering online
BACKGROUND: An efficient and accurate approach to quantify the steatosis extent of liver is important for clinical practice. For the purpose, we propose a specific designed ultrasound shear wave sequence to estimate ultrasonic and shear wave physical...

Submillimeter MR fingerprinting using deep learning-based tissue quantification.

Magnetic resonance in medicine
PURPOSE: To develop a rapid 2D MR fingerprinting technique with a submillimeter in-plane resolution using a deep learning-based tissue quantification approach.

Accurate Deep Learning-Based Sleep Staging in a Clinical Population With Suspected Obstructive Sleep Apnea.

IEEE journal of biomedical and health informatics
The identification of sleep stages is essential in the diagnostics of sleep disorders, among which obstructive sleep apnea (OSA) is one of the most prevalent. However, manual scoring of sleep stages is time-consuming, subjective, and costly. To overc...

A hybrid automated treatment planning solution for esophageal cancer.

Radiation oncology (London, England)
OBJECTIVE: This study aims to investigate a hybrid automated treatment planning (HAP) solution that combines knowledge-based planning (KBP) and script-based planning for esophageal cancer.