Fibromyalgia

Driver Fatigue Detection Based on Convolutional Neural Networks Using EM-CNN.

With a focus on fatigue driving detection research, a fully automated driver fatigue status detection algorithm using driving images is proposed. In the proposed algorithm, the multitask cascaded convolutional network (MTCNN) architecture is employed in face detection and feature point location, and the region of interest (ROI) is extracted using feature points. A convolutional neural network, nam...

Optimization technique combined with deep learning method for teeth recognition in dental panoramic radiographs.

Computer-assisted analysis of dental radiograph in dentistry is getting increasing attention from the researchers in recent years. This is mainly because it can successfully reduce human-made error due to stress, fatigue or lack of experience. Furthermore, it reduces diagnosis time and thus, improves overall efficiency and accuracy of dental care system. An automatic teeth recognition model is pro...

FUSI-CAD: Coronavirus (COVID-19) diagnosis based on the fusion of CNNs and handcrafted features.

The precise and rapid diagnosis of coronavirus (COVID-19) at the very primary stage helps doctors to manage patients in high workload conditions. In a...

Aerobic Fitness is a Predictor of Body Composition in Women With Breast Cancer at Diagnosis.

BACKGROUND: The objective of this study was to investigate the relationship of aerobic fitness (AF) at diagnosis, before treatment and its relationshi...

Efficient and Effective Training of COVID-19 Classification Networks With Self-Supervised Dual-Track Learning to Rank.

Coronavirus Disease 2019 (COVID-19) has rapidly spread worldwide since first reported. Timely diagnosis of COVID-19 is crucial both for disease contro...

Discriminating between sleep and exercise-induced fatigue using computer vision and behavioral genetics.

Following prolonged swimming, cycle between active swimming bouts and inactive quiescent bouts. Swimming is exercise for and here we suggest that in...

A Deep-Learning Approach for Foot-Type Classification Using Heterogeneous Pressure Data.

The human foot is easily deformed owing to the innate form of the foot or an incorrect walking posture. Foot deformations not only pose a threat to fo...

Esophagus segmentation from planning CT images using an atlas-based deep learning approach.

BACKGROUND AND OBJECTIVE: One of the main steps in the planning of radiotherapy (RT) is the segmentation of organs at risk (OARs) in Computed Tomograp...

ADR-Net: Context extraction network based on M-Net for medical image segmentation.

PURPOSE: Medical image segmentation is an essential component of medical image analysis. Accurate segmentation can assist doctors in diagnosis and rel...

Is there any association between low level of serum nesfatin-1 and fibromyalgia syndrome?

OBJECTIVES: This study aims to investigate the relationship between serum level of nesfatin-1 and fibromyalgia syndrome (FMS) clinical parameters such...

Adaptive robot mediated upper limb training using electromyogram-based muscle fatigue indicators.

Studies on improving the adaptability of upper limb rehabilitation training do not often consider the implications of muscle fatigue sufficiently. In ...

Parametric investigation of the effects of load level on fatigue crack growth in trabecular bone based on artificial neural network computation.

This study reports the development of an artificial neural network computation model to predict the accumulation of crack density and crack length in ...

EEG Signal and Feature Interaction Modeling-Based Eye Behavior Prediction Research.

In recent years, with the development of brain science and biomedical engineering, as well as the rapid development of electroencephalogram (EEG) sign...

A generalized predictive control for remote cardiovascular surgical systems.

Robot-assisted cardiovascular surgery is used to avoid surgeon suffering from X-ray radiation and relieve fatigue caused by long-time standing wearing...

Flexoskeleton Printing Enables Versatile Fabrication of Hybrid Soft and Rigid Robots.

One of the many secrets to the success and prevalence of insects is their versatile, robust, and complex exoskeleton morphology. A fundamental challen...

Deep learning approaches for sleep disorder prediction in an asthma cohort.

OBJECTIVE: Sleep is a natural activity of humans that affects physical and mental health; therefore, sleep disturbance may lead to fatigue and lower p...

Machine Learning Diagnostic Modeling for Classifying Fibromyalgia Using B-mode Ultrasound Images.

Fibromyalgia (FM) diagnosis remains a challenge for clinicians due to a lack of objective diagnostic tools. One proposed solution is the use of quanti...

Early prediction of circulatory failure in the intensive care unit using machine learning.

Intensive-care clinicians are presented with large quantities of measurements from multiple monitoring systems. The limited ability of humans to proce...

A review of methods for achieving upper limb movement following spinal cord injury through hybrid muscle stimulation and robotic assistance.

Individuals with tetraplegia, typically attributed to spinal cord injuries (SCI) at the cervical level, experience significant health care costs and l...

Control of Functional Electrical Stimulation Systems Using Simultaneous Pulse Width, Amplitude, and Frequency Modulations.

BACKGROUND: One significant challenge of developing a controller for functional electrical stimulation systems is the time-variant nonlinear dynamics ...