AIMC Topic: Young Adult
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Artificial Intelligence for Objective Assessment of Acrobatic Movements: Applying Machine Learning for Identifying Tumbling Elements in Cheer Sports.
Sensors (Basel, Switzerland)
Apr 3, 2025
Over the past four decades, cheerleading evolved from a sideline activity at major sporting events into a professional, competitive sport with growing global popularity. Evaluating tumbling elements in cheerleading relies on both objective measures a...
Can artificial ıntelligence detect the anti-aging effect of rhinoplasty?
Journal of plastic surgery and hand surgery
Apr 3, 2025
BACKGROUND: The quest for eternal youth has been a common theme in many cultures for centuries. While we have yet to discover a way to preserve youth eternally, we have made significant progress in understanding the aging process and in developing ph...
Machine learning-based non-invasive continuous dynamic monitoring of human core temperature with wearable dual temperature sensors.
Physiological measurement
Apr 3, 2025
Due to the growing demand for personal health monitoring in extreme environments, continuous monitoring of core temperature has become increasingly important. Traditional monitoring methods, such as mercury thermometers and infrared thermometers, may...
Positive relationship between education level and risk perception and behavioral response: A machine learning approach.
PloS one
Apr 3, 2025
This paper aims to examine the influence mechanism of education level as a key situational factor in the relationship between risk perception and behavioral response, encompassing both behavioral intention and preparatory behavior. Utilizing non-para...
Random forest and Shapley Additive exPlanations predict oxytocin targeted effects on brain functional networks involved in salience and sensorimotor processing, in a randomized clinical trial in autism.
Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
Apr 2, 2025
Intranasal oxytocin (IN-OXT) has shown some promises in rescuing social deficits in autism spectrum disorder (ASD) as well as some inconsistencies in long-term trials. We conducted a target engagement study to study the precise effects of different d...
Neural networks can accurately identify individual runners from their foot kinematics, but fail to predict their running performance.
Journal of biomechanics
Apr 2, 2025
Athletes and coaches may seek to improve running performance through adjustments to running form. Running form refers to the biomechanical characteristics of a runner's movement, and can distinguish individual runners as well as groups of runners, su...
A validity and reliability study of the artificial intelligence attitude scale (AIAS-4) and its relationship with social media addiction and eating behaviors in Turkish adults.
BMC public health
Apr 2, 2025
BACKGROUND: In recent years, there has been a rapid increase in the use of the internet and social media. Billions of people worldwide use social media and spend an average of 2.2 h a day on these platforms. At the same time, artificial intelligence ...
Computer vision and tactile glove: A multimodal model in lifting task risk assessment.
Applied ergonomics
Apr 1, 2025
Work-related injuries from overexertion, particularly lifting, are a major concern in occupational safety. Traditional assessment tools, such as the Revised NIOSH Lifting Equation (RNLE), require significant training and practice for deployment. This...
Enhancing brain age estimation under uncertainty: A spectral-normalized neural gaussian process approach utilizing 2.5D slicing.
NeuroImage
Apr 1, 2025
Brain age gap, the difference between estimated brain age and chronological age via magnetic resonance imaging, has emerged as a pivotal biomarker in the detection of brain abnormalities. While deep learning is accurate in estimating brain age, the a...
Using 3D Convolutional Neural Network and Corvis ST Corneal Dynamic Video for Detecting Forme Fruste Keratoconus.
Journal of refractive surgery (Thorofare, N.J. : 1995)
Apr 1, 2025
PURPOSE: To evaluate the performance of a three-dimensional convolutional neural network (3D CNN) in detecting forme fruste keratoconus (FFKC).
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