AIMC Topic: Male

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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...

Growth Inhibitory and Pro-Apoptotic Effects of Ornamental Pomegranate Extracts in Du145 Human Prostate Cancer Cells.

Nutrition and cancer
Prostate cancer is the most common form of cancer in the male. Epidemiological studies have associated increased cancer incidence with reduced consumption of fruit and vegetables. This study was aimed to investigate the influence of dwarf pomegranat...

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...

A probabilistic method to estimate gait kinetics in the absence of ground reaction force measurements.

Journal of biomechanics
Human joint torques during gait are usually computed using inverse dynamics. This method requires a skeletal model, kinematics and measured ground reaction forces and moments (GRFM). Measuring GRFM is however only possible in a controlled environment...

Machine learning algorithms can classify outdoor terrain types during running using accelerometry data.

Gait & posture
BACKGROUND: Running is a popular physical activity that benefits health; however, running surface characteristics may influence loading impact and injury risk. Machine learning algorithms could automatically identify running surface from wearable mot...

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...