AIMC Topic: Fatigue

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Machine learning analysis based on deep learning for fatigue diagnostics in carbon fiber reinforced polymers.

PloS one
Fatigue-induced degradation in Carbon Fiber Reinforced Polymer (CFRP) structures poses a critical challenge in long-term structural health monitoring (SHM) applications. In this study, a hybrid deep learning framework is proposed for fatigue state cl...

Development and validation of a machine learning model to predict moderate-to-severe cancer-related fatigue in breast cancer.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: This study aimed to establish and validate a machine learning model for predicting moderate-to-severe cancer-related fatigue (CRF) 2 years after completion of anti-tumor therapy in breast cancer patients.

Advancing training effectiveness prediction in mass sport through longitudinal data: A mathematical model approach based on the Fitness-Fatigue Model.

PloS one
Despite the critical need for scientific training load assessment in mass sports, the Fitness-Fatigue Model (FFM) requires further mathematical optimization and practical output indicators. The aim of this study was to optimize the mathematical relat...

Perceived fatigue progression tracking during manual handling tasks using sEMG recordings.

Journal of neuroengineering and rehabilitation
Physical fatigue significantly contributes to work-related musculoskeletal disorders, highlighting the need to understand its effects during manual handling tasks for effective prevention strategies. This study examines the correlation between change...

FatigueNet: A hybrid graph neural network and transformer framework for real-time multimodal fatigue detection.

Scientific reports
Fatigue creates complex challenges that present themselves through cognitive problems alongside physical impacts and emotional consequences. FatigueNet represents a modern multimodal framework that deals with two main weaknesses in present-day fatigu...

Construction of a predictive model for the risk of moderate-to-severe cancer-related fatigue in colorectal cancer chemotherapy patients: an interpretable machine learning approach.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: This study aimed to analyze the influencing factors of moderate-to-severe cancer-related fatigue (CRF) in colorectal cancer (CRC) chemotherapy patients and to develop a predictive risk stratification model.

Impact of Preseason Training Camps on Fitness, Fatigue, and Performance in Professional Football Players: Mildaltitude Camp Versus Sea-Level Camp.

International journal of sports physiology and performance
PURPOSE: Preseason in football is crucial for optimizing physical fitness, team cohesion, and tactical readiness. This study investigated the effects of 2 distinct preseason training environments-mild altitude with cooler conditions and sea level wit...

Fatigue and stamina prediction of athletic person on track using thermal facial biomarkers and optimized machine learning algorithm.

Scientific reports
Athletic person's fatigue and stamina prediction plays a vital role for improving the overall performance in the sports. Identification of the athletic person's facial expression on track and field using image, is still a challenge task. The complex ...

A machine learning model using clinical notes to identify physician fatigue.

Nature communications
Clinical notes should capture important information from a physician-patient encounter, but they may also contain signals indicative of physician fatigue. Using data from 129,228 emergency department (ED) visits, we train a model to identify notes wr...

Fatigue monitoring using wearables and AI: Trends, challenges, and future opportunities.

Computers in biology and medicine
Monitoring fatigue is essential for improving safety, particularly for people who work long shifts or in high-demand and high-risk environments such as transportation, construction, healthcare, and manufacturing. The development of wearable technolog...