AIMC Topic: Adult

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Estimation of absolute states of human skeletal muscle via standard B-mode ultrasound imaging and deep convolutional neural networks.

Journal of the Royal Society, Interface
The objective is to test automated estimation of active and passive skeletal muscle states using ultrasonic imaging. Current technology (electromyography, dynamometry, shear wave imaging) provides no general, non-invasive method for online estimatio...

Does robot-assisted gait training improve mobility, activities of daily living and quality of life in stroke? A single-blinded, randomized controlled trial.

Acta neurologica Belgica
The purpose of this study was to investigate the effects of robot-assisted gait training (RAGT) on mobility, activities of daily living (ADLs), and quality of life (QoL) in stroke rehabilitation. Fifty-one stroke patients randomly assigned to Group 1...

Automatic versus manual tuning of robot-assisted gait training in people with neurological disorders.

Journal of neuroengineering and rehabilitation
BACKGROUND: In clinical practice, therapists choose the amount of assistance for robot-assisted training. This can result in outcomes that are influenced by subjective decisions and tuning of training parameters can be time-consuming. Therefore, vari...

Automated classification of normal and Stargardt disease optical coherence tomography images using deep learning.

Acta ophthalmologica
PURPOSE: Recent advances in deep learning have seen an increase in its application to automated image analysis in ophthalmology for conditions with a high prevalence. We wanted to identify whether deep learning could be used for the automated classif...

Machine learning validation of EEG+tACS artefact removal.

Journal of neural engineering
OBJECTIVE: Electroencephalography (EEG) recorded during transcranial alternating current simulation (tACS) is highly desirable in order to investigate brain dynamics during stimulation, but is corrupted by large amplitude stimulation artefacts. Artef...

Observer-independent assessment of psoriasis-affected area using machine learning.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Assessment of psoriasis severity is strongly observer-dependent, and objective assessment tools are largely missing. The increasing number of patients receiving highly expensive therapies that are reimbursed only for moderate-to-severe ps...

Design of a deep learning model for automatic scoring of periodic and non-periodic leg movements during sleep validated against multiple human experts.

Sleep medicine
OBJECTIVE: Currently, manual scoring is the gold standard of leg movement scoring (LMs) and periodic LMs (PLMS) in overnight polysomnography (PSG) studies, which is subject to inter-scorer variability. The objective of this study is to design and val...

Quantitative Thermal Imaging Biomarkers to Detect Acute Skin Toxicity From Breast Radiation Therapy Using Supervised Machine Learning.

International journal of radiation oncology, biology, physics
PURPOSE: Radiation-induced dermatitis is a common side effect of breast radiation therapy (RT). Current methods to evaluate breast skin toxicity include clinical examination, visual inspection, and patient-reported symptoms. Physiological changes ass...

Coronary Artery Disease Diagnosis; Ranking the Significant Features Using a Random Trees Model.

International journal of environmental research and public health
Heart disease is one of the most common diseases in middle-aged citizens. Among the vast number of heart diseases, coronary artery disease (CAD) is considered as a common cardiovascular disease with a high death rate. The most popular tool for diagno...