AIMC Topic: Young Adult
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Machine learning models in evaluating the malignancy risk of ovarian tumors: a comparative study.
Journal of ovarian research
Nov 6, 2024
OBJECTIVES: The study aimed to compare the diagnostic efficacy of the machine learning models with expert subjective assessment (SA) in assessing the malignancy risk of ovarian tumors using transvaginal ultrasound (TVUS).
Computed tomography enterography radiomics and machine learning for identification of Crohn's disease.
BMC medical imaging
Nov 6, 2024
BACKGROUND: Crohn's disease is a severe chronic and relapsing inflammatory bowel disease. Although contrast-enhanced computed tomography enterography is commonly used to evaluate crohn's disease, its imaging findings are often nonspecific and can ove...
During haptic communication, the central nervous system compensates distinctly for delay and noise.
PLoS computational biology
Nov 6, 2024
Physically connected humans have been shown to exploit the exchange of haptic forces and tactile information to improve their performance in joint action tasks. As human interactions are increasingly mediated through robots and networks it is importa...
ECG Biometric Authentication Using Self-Supervised Learning for IoT Edge Sensors.
IEEE journal of biomedical and health informatics
Nov 6, 2024
Wearable Internet of Things (IoT) devices are gaining ground for continuous physiological data acquisition and health monitoring. These physiological signals can be used for security applications to achieve continuous authentication and user convenie...
Off-Body Sleep Analysis for Predicting Adverse Behavior in Individuals With Autism Spectrum Disorder.
IEEE journal of biomedical and health informatics
Nov 6, 2024
Poor sleep quality in Autism Spectrum Disorder (ASD) individuals is linked to severe daytime behaviors. This study explores the relationship between a prior night's sleep structure and its predictive power for next-day behavior in ASD individuals. Th...
Predicting Continuous Locomotion Modes via Multidimensional Feature Learning From sEMG.
IEEE journal of biomedical and health informatics
Nov 6, 2024
Walking-assistive devices require adaptive control methods to ensure smooth transitions between various modes of locomotion. For this purpose, detecting human locomotion modes (e.g., level walking or stair ascent) in advance is crucial for improving ...
Multi-Loss Disentangled Generative-Discriminative Learning for Multimodal Representation in Schizophrenia.
IEEE journal of biomedical and health informatics
Nov 6, 2024
Schizophrenia (SCZ) is a multifactorial mental illness, thus it will be beneficial for exploring this disease using multimodal data, including functional magnetic resonance imaging (fMRI), genes, and the gut microbiome. Previous studies reported comb...
Circulating endothelial progenitor cells and inflammatory markers in type 1 diabetes after an acute session of aerobic exercise.
Archives of endocrinology and metabolism
Nov 6, 2024
OBJECTIVE: To determine circulating endothelial progenitor cells (EPC) counts and levels of inflammatory markers in individuals with and without type 1 diabetes mellitus (T1DM) in response to an intense aerobic exercise session.
Lower Limb Torque Prediction for Sit-To-Walk Strategies Using Long Short-Term Memory Neural Networks.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Nov 6, 2024
Joint torque prediction is crucial when investigating biomechanics, evaluating treatments, and designing powered assistive devices. Controllers in assistive technology require reference torque trajectories to set the level of assistance for a patient...
Detecting Emotional Arousal and Aggressive Driving Using Neural Networks: A Pilot Study Involving Young Drivers in Duluth.
Sensors (Basel, Switzerland)
Nov 5, 2024
Driving is integral to many people's daily existence, but aggressive driving behavior increases the risk of road traffic collisions. Young drivers are more prone to aggressive driving and danger perception impairments. A driver's physiological state ...
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