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Classification of needle-EMG resting potentials by machine learning.

Muscle & nerve
INTRODUCTION: The diagnostic importance of audio signal characteristics in needle electromyography (EMG) is well established. Given the recent advent of audio-sound identification by artificial intelligence, we hypothesized that the extraction of cha...

Automated classification of Alzheimer's disease and mild cognitive impairment using a single MRI and deep neural networks.

NeuroImage. Clinical
We built and validated a deep learning algorithm predicting the individual diagnosis of Alzheimer's disease (AD) and mild cognitive impairment who will convert to AD (c-MCI) based on a single cross-sectional brain structural MRI scan. Convolutional n...

Combining multimodal imaging and treatment features improves machine learning-based prognostic assessment in patients with glioblastoma multiforme.

Cancer medicine
BACKGROUND: For Glioblastoma (GBM), various prognostic nomograms have been proposed. This study aims to evaluate machine learning models to predict patients' overall survival (OS) and progression-free survival (PFS) on the basis of clinical, patholog...

Degradation of TRPML1 in Neurons Reduces Neuron Survival in Transient Global Cerebral Ischemia.

Oxidative medicine and cellular longevity
Postcardiac arrest syndrome yields poor neurological outcomes, but the mechanisms underlying this condition remain poorly understood. Autophagy plays an important role in neuronal apoptosis induced by ischemia. However, whether autophagy is involved ...

Measuring Oxygen Saturation With Smartphone Cameras Using Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Arterial oxygen saturation ([Formula: see text]) is an indicator of how much oxygen is carried by hemoglobin in the blood. Having enough oxygen is vital for the functioning of cells in the human body. Measurement of [Formula: see text] is typically e...

A Dual Mode Adaptive Basal-Bolus Advisor Based on Reinforcement Learning.

IEEE journal of biomedical and health informatics
Self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM) are commonly used by type 1 diabetes (T1D) patients to measure glucose concentrations. The proposed adaptive basal-bolus algorithm (ABBA) supports inputs from either SMBG...

Assistive robots for socialization in elderly people: results pertaining to the needs of the users.

Aging clinical and experimental research
BACKGROUND/AIM: Technological solutions can support the elderly, improve their quality of life and reduce isolation and loneliness. The Euro-Japan ACCRA (Agile Co-Creation for Robots and Aging) project has the objective of building a reference co-cre...

Quantitative ultrasound and machine learning for assessment of steatohepatitis in a rat model.

European radiology
OBJECTIVES: To develop a machine learning model based on quantitative ultrasound (QUS) parameters to improve classification of steatohepatitis with shear wave elastography in rats by using histopathology scoring as the reference standard.

Ultra-Low-Dose Neck CT With Low-Dose Contrast Material for Preoperative Staging of Thyroid Cancer: Image Quality and Diagnostic Performance.

AJR. American journal of roentgenology
OBJECTIVE: Although CT has been used as a complementary diagnostic method for the preoperative diagnosis of thyroid cancer, it has the shortcomings of substantial radiation exposure and the use of contrast material (CM). The purpose of this article i...

A hypothetical neural network model for generation of human precision grip.

Neural networks : the official journal of the International Neural Network Society
Humans can stably hold and skillfully manipulate an object by coordinated control of a complex, redundant musculoskeletal system. However, how the human central nervous system actually accomplishes precision grip tasks by coordinated control of finge...