Fibromyalgia

A Machine Learning Approach to Classifying Self-Reported Health Status in a Cohort of Patients With Heart Disease Using Activity Tracker Data.

Constructing statistical models using personal sensor data could allow for tracking health status over time, thereby enabling the possibility of early intervention. The goal of this study was to use machine learning algorithms to classify patient-reported outcomes (PROs) using activity tracker data in a cohort of patients with stable ischemic heart disease (SIHD). A population of 182 patients with...

Differences in muscle activity and fatigue of the upper limb between Task-Specific training and robot assisted training among individuals post stroke.

OBJECTIVE: To compare the activity and fatigue of upper extremity muscles, pain levels, subject satisfaction levels, perceived exertion, and number of repetitions in Task-Specific Training (TST) compared with Robot-Assisted Training (RAT) in individuals post-stroke.

Artificial intelligence based discovery of the association between depression and chronic fatigue syndrome.

BACKGROUND: Both of the modern medicine and the traditional Chinese medicine classify depressive disorder (DD) and chronic fatigue syndrome (CFS) to o...

Hybrid Rehabilitation Therapies on Upper-Limb Function and Goal Attainment in Chronic Stroke.

This study examined the treatment effects between unilateral hybrid therapy (UHT; unilateral robot-assisted therapy [RT] + modified constraint-induced...

The Importance of G-protein Coupled Estrogen Receptor in Patients With Fibromyalgia.

OBJECTIVES: This study aims to analyze the G-protein coupled estrogen receptor (GPER/GPR30) activity in patients with fibromyalgia syndrome (FMS).

EEG-Based Spatio-Temporal Convolutional Neural Network for Driver Fatigue Evaluation.

Driver fatigue evaluation is of great importance for traffic safety and many intricate factors would exacerbate the difficulty. In this paper, based o...

Estimating Prevalence, Demographics, and Costs of ME/CFS Using Large Scale Medical Claims Data and Machine Learning.

Techniques of data mining and machine learning were applied to a large database of medical and facility claims from commercially insured patients to d...

Automated Cell Counts on Tissue Sections by Deep Learning and Unbiased Stereology.

In recent decades stereology-based studies have played a significant role in understanding brain aging and developing novel drug discovery strategies ...

Deep Learning-Based Detection of Intracranial Aneurysms in 3D TOF-MRA.

BACKGROUND AND PURPOSE: The rupture of an intracranial aneurysm is a serious incident, causing subarachnoid hemorrhage associated with high fatality a...

Muscle fatigue assessment during robot-mediated movements.

BACKGROUND: Several neuromuscular disorders present muscle fatigue as a typical symptom. Therefore, a reliable method of fatigue assessment may be cru...

Distributed Repetitive Learning Control for Cooperative Cadence Tracking in Functional Electrical Stimulation Cycling.

Closed-loop control of functional electrical stimulation coupled with motorized assistance to induce cycling is a rehabilitative strategy that can imp...

Neural network analysis of Chinese herbal medicine prescriptions for patients with colorectal cancer.

Traditional Chinese Medicine (TCM) is an experiential form of medicine with a history dating back thousands of years. The present study aimed to utili...

Hispaglabridin B, a constituent of liquorice identified by a bioinformatics and machine learning approach, relieves protein-energy wasting by inhibiting forkhead box O1.

BACKGROUND AND PURPOSE: Liquorice is the root of Glycyrrhiza glabra, which is a popular food in Europe and China that has previously shown benefits fo...

Supervised machine learning to decipher the complex associations between neuro-immune biomarkers and quality of life in schizophrenia.

Stable phase schizophrenia is characterized by altered patterning in tryptophan catabolites (TRYCATs) and memory impairments, which are associated wit...

Hand Exo-Muscular System for Assisting Astronauts During Extravehicular Activities.

Human exploration of the Solar System is one of the most challenging objectives included in the space programs of the most important space agencies in...

Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists.

BACKGROUND: Chest radiograph interpretation is critical for the detection of thoracic diseases, including tuberculosis and lung cancer, which affect m...

Improving Performance of Devanagari Script Input-Based P300 Speller Using Deep Learning.

The performance of an existing Devanagari script (DS) input-based P300 speller with conventional machine learning techniques suffers from low informat...

Aiding the Digital Mammogram for Detecting the Breast Cancer Using Shearlet Transform and Neural Network.

Objective: Breast Cancer is the most invasive disease and fatal disease next to lung cancer in human. Early detection of breast cancer is accomplished...

Modeling Neural Adaptation in Auditory Cortex.

Neural responses recorded from auditory cortex exhibit adaptation, a stimulus-specific decrease that occurs when the same sound is presented repeatedl...

A rapid LC-MS/MS method for simultaneous determination of quetiapine and duloxetine in rat plasma and its application to pharmacokinetic interaction study.

Combinations of new antidepressants like duloxetine and second-generation antipsychotics like quetiapine are used in clinical treatment of major depre...