AIMC Topic: Middle Aged

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Nonconvulsive epileptic seizure monitoring with incremental learning.

Computers in biology and medicine
Nonconvulsive epileptic seizures (NCSz) and nonconvulsive status epilepticus (NCSE) are two neurological entities associated with increment in morbidity and mortality in critically ill patients. In a previous work, we introduced a method which accura...

Fore-aft resistance applied at the center of mass using a novel robotic interface proportionately increases propulsive force generation in healthy nonimpaired individuals walking at a constant speed.

Journal of neuroengineering and rehabilitation
BACKGROUND: Past studies have utilized external interfaces like resistive bands and motor-generated pulling systems to increase limb propulsion during walking on a motorized treadmill. However, assessing changes in limb propulsion against increasing ...

Uncovering convolutional neural network decisions for diagnosing multiple sclerosis on conventional MRI using layer-wise relevance propagation.

NeuroImage. Clinical
Machine learning-based imaging diagnostics has recently reached or even surpassed the level of clinical experts in several clinical domains. However, classification decisions of a trained machine learning system are typically non-transparent, a major...

Two-step deep neural network for segmentation of deep white matter hyperintensities in migraineurs.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Patients with migraine show an increased presence of white matter hyperintensities (WMHs), especially deep WMHs. Segmentation of small, deep WMHs is a critical issue in managing migraine care. Here, we aim to develop a novel...

CT Texture Analysis and Machine Learning Improve Post-ablation Prognostication in Patients with Adrenal Metastases: A Proof of Concept.

Cardiovascular and interventional radiology
INTRODUCTION: To assess the performance of pre-ablation computed tomography texture features of adrenal metastases to predict post-treatment local progression and survival in patients who underwent ablation using machine learning as a prediction tool...

Automatic segmentation of the uterus on MRI using a convolutional neural network.

Computers in biology and medicine
BACKGROUND: This study was performed to evaluate the clinical feasibility of a U-net for fully automatic uterine segmentation on MRI by using images of major uterine disorders.

Machine-learning-based classification between post-traumatic stress disorder and major depressive disorder using P300 features.

NeuroImage. Clinical
BACKGROUND: The development of optimal classification criteria for specific mental disorders which share similar symptoms is an important issue for precise diagnosis. We investigated whether P300 features in both sensor-level and source-level could b...

The effect of using Gait Exercise Assist Robot (GEAR) on gait pattern in stroke patients: a cross-sectional pilot study.

Topics in stroke rehabilitation
: The Gait Exercise Assist Robot (GEAR) has been developed to support gait training for stroke patients. The GEAR can assist paretic lower limb swing and stance stability, which make it possible to practice walking without excessive compensation move...