AIMC Topic: Young Adult

Clear Filters Showing 21 to 30 of 4791 articles

Leveraging deep learning for the detection of socially desirable tendencies in personnel selection: A proof-of-concept.

PloS one
We propose a deep learning-based method for detecting Socially Desirable Responding (SDR)-the tendency for individuals to distort questionnaire responses to present themselves in a favorable light. Our objective is to showcase that such novel methods...

Machine learning of whole-brain resting-state fMRI signatures for individualized grading of frontal gliomas.

Cancer imaging : the official publication of the International Cancer Imaging Society
PURPOSE: Accurate preoperative grading of gliomas is critical for therapeutic planning and prognostic evaluation. We developed a noninvasive machine learning model leveraging whole-brain resting-state functional magnetic resonance imaging (rs-fMRI) b...

Enhanced gastrocnemius-mimicking lower limb powered exoskeleton robot.

Journal of neuroengineering and rehabilitation
BACKGROUND: Lower limb muscle bionic devices have attracted significant attention in rehabilitation and assistive sports technology. Despite advancements in mimicking human movement, current devices still face challenges in enhancing strength and mov...

Unsupervised machine learning approach to interpret complex lower urinary tract symptoms and their impact on quality of life in adult women.

World journal of urology
PURPOSE: To identify clinically meaningful clusters of lower urinary tract symptoms (LUTS) in adult women using an unsupervised machine learning approach and to examine their associations with patient-centered outcomes, including quality of life (QoL...

Internet of things enabled deep learning monitoring system for realtime performance metrics and athlete feedback in college sports.

Scientific reports
This study presents an Internet of Things (IoT)-enabled Deep Learning Monitoring (IoT-E-DLM) model for real-time Athletic Performance (AP) tracking and feedback in collegiate sports. The proposed work integrates advanced wearable sensor technologies ...

The Predictive Value of Serum Total IgE for Antihistamine Treatment Outcomes in Chinese Patients with Chronic Spontaneous Urticaria.

Acta dermato-venereologica
Chronic spontaneous urticaria is a common skin disorder with variable treatment responses. Second-generation H1-antihistamines are the first-line treatment for chronic spontaneous urticaria, yet many patients fail to respond to licensed doses. Predic...

Predicting academic performance with fuzzy logic in prospective physical education and sports teachers.

Scientific reports
Numerous factors contribute to student success in educational settings, with academic support and learning strategies identified as key influences. Existing research highlights that various academic assistance and individual learning approaches shape...

METS-VF as a novel predictor of gallstones in U.S. adults: a cross-sectional analysis (NHANES 2017-2020).

BMC gastroenterology
BACKGROUND AND AIMS: Obesity is a well-established risk factor for gallstone formation, but traditional anthropometric measures (e.g., BMI, waist circumference) inadequately assess metabolically active visceral adiposity. The novel Metabolic Score fo...

Classification accuracy of pain intensity induced by leg blood flow restriction during walking using machine learning based on electroencephalography.

Scientific reports
Pain assessment in clinical practice largely relies on patient-reported subjectivity. Although previous studies using fMRI and EEG have attempted objective pain evaluation, their focus has been limited to resting conditions. This study aimed to class...

Influencing factors and dynamic changes of COVID-19 vaccine hesitancy in China: From the perspective of machine learning analysis.

Human vaccines & immunotherapeutics
Exploring the influencing factors of COVID-19 vaccine hesitancy and summarizing countermeasures is of great significance for effectively addressing potential public health crises. Based on survey data from China, we employed a Gradient Boosting Decis...