AIMC Topic: Fatigue

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Performance of machine learning models for predicting high-severity symptoms in multiple sclerosis.

Scientific reports
Current care in multiple sclerosis (MS) primarily relies on infrequently obtained data such as magnetic resonance imaging, clinical laboratory tests or clinical history, resulting in subtle changes that may occur between visits being missed. Mobile t...

Identifying Symptom Information in Clinical Notes Using Natural Language Processing.

Nursing research
BACKGROUND: Symptoms are a core concept of nursing interest. Large-scale secondary data reuse of notes in electronic health records (EHRs) has the potential to increase the quantity and quality of symptom research. However, the symptom language used ...

An exploratory analysis of longitudinal artificial intelligence for cognitive fatigue detection using neurophysiological based biosignal data.

Scientific reports
Cognitive fatigue is a psychological condition characterized by opinions of fatigue and weakened cognitive functioning owing to constant stress. Cognitive fatigue is a critical condition that can significantly impair attention and performance, among ...

Fatigue Detection with Machine Learning Approaches using Data from Wearable Devices.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Severe and chronic fatigue is one of the top symptoms in patients with non-communicable chronic immune-mediated inflammatory diseases like Systemic Lupus Erythematosus (SLE) and Sjögren's disease (SjD). The majority of fatigue assessment approaches r...

Using Natural Language Processing to Extract and Classify Symptoms Among Patients with Thyroid Dysfunction.

Studies in health technology and informatics
In the United States, more than 12% of the population will experience thyroid dysfunction. Patient symptoms often reported with thyroid dysfunction include fatigue and weight change. However, little is understood about the relationship between these ...

Bio-signals Collecting System for Fatigue Level Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Fatigue is a risk factor that reduces quality of life and work efficiency, and threatens safety in a high-risk environment. However, fatigue is not yet precisely defined and is not a quantified concept as it relies on subjective evaluation. The purpo...

Deep Learning for Cancer Symptoms Monitoring on the Basis of Electronic Health Record Unstructured Clinical Notes.

JCO clinical cancer informatics
PURPOSE: Symptoms are vital outcomes for cancer clinical trials, observational research, and population-level surveillance. Patient-reported outcomes (PROs) are valuable for monitoring symptoms, yet there are many challenges to collecting PROs at sca...

Predicting Future Perceived Wellness in Professional Soccer: The Role of Preceding Load and Wellness.

International journal of sports physiology and performance
PURPOSE: The influence of preceding load and future perceived wellness of professional soccer players is unexamined. This paper simultaneously evaluates the external load (EL) and internal load (IL) for different time frames in combination with prese...

Feasibility study: Towards Estimation of Fatigue Level in Robot-Assisted Exercise for Cardiac Rehabilitation.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Socially Assistive Robotics (SAR) has shown to be an important tool to assist patients in physical rehabilitation. SAR is used to provide feedback about patient's state and performance to users and health professionals, therefore, patients are monito...