Statistical learning, the ability to extract regularities from the environment over time, has become a topic of burgeoning interest. Its influence on behavior, spanning infancy to adulthood, has been demonstrated across a range of tasks, both those labeled as tests of statistical learning and those from other learning domains that predated statistical learning research or that are not typically considered in the context of that literature. Given this pervasive role in human cognition, statistical learning has the potential to reconcile seemingly distinct learning phenomena and may be an under-appreciated but important contributor to a wide range of human behaviors that are studied as unrelated processes, such as episodic memory and spatial navigation.
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http://dx.doi.org/10.1016/j.cobeha.2020.01.015 | DOI Listing |
BMC Public Health
January 2025
Statistics, Brigham Young University, Provo, 84602, Utah, USA.
Background: Bullying, encompassing physical, psychological, social, or educational harm, affects approximately 1 in 20 United States teens aged 12-18. The prevalence and impact of bullying, including online bullying, necessitate a deeper understanding of risk and protective factors to enhance prevention efforts. This study investigated the key risk and protective factors most highly associated with adolescent bullying victimization.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Anesthesiology and Surgical Intensive Care Unit, Kunming Children's Hospital, Kunming, Yunnan, China.
Metabolic syndrome (Mets) in adolescents is a growing public health issue linked to obesity, hypertension, and insulin resistance, increasing risks of cardiovascular disease and mental health problems. Early detection and intervention are crucial but often hindered by complex diagnostic requirements. This study aims to develop a predictive model using NHANES data, excluding biochemical indicators, to provide a simple, cost-effective tool for large-scale, non-medical screening and early prevention of adolescent MetS.
View Article and Find Full Text PDFAm J Orthod Dentofacial Orthop
February 2025
Department of Orthodontics, Faculty of Dentistry, Çanakkale Onsekiz Mart University, Çanakkale, Turkey.
Introduction: This study aimed to assess the precision of an open-source, clinician-trained, and user-friendly convolutional neural network-based model for automatically segmenting the mandible.
Methods: A total of 55 cone-beam computed tomography scans that met the inclusion criteria were collected and divided into test and training groups. The MONAI (Medical Open Network for Artificial Intelligence) Label active learning tool extension was used to train the automatic model.
J Prev Alzheimers Dis
February 2025
Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA; Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA; School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA.
Background: Recent disease-modifying treatments for Alzheimer's disease show promise to slow cognitive decline, but show no efficacy towards reducing symptoms already manifested.
Objectives: To investigate the efficacy of a novel noninvasive brain stimulation technique in modulating cognitive functioning in Alzheimer's dementia (AD).
Design: Pilot, randomized, double-blind, parallel, sham-controlled study SETTING: Clinical research site at UT Southwestern Medical Center PARTICIPANTS: Twenty-five participants with clinical diagnoses of AD were enrolled from cognition specialty clinics.
J Immunother Cancer
January 2025
Section of Nephrology, Division of Internal Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
Immune checkpoint inhibitor (ICI) therapy is a cornerstone treatment for many cancers, but it can induce severe immunotoxicity, including acute interstitial nephritis (AIN). Currently, kidney biopsy is required to differentiate ICI-AIN from other causes of acute kidney injury (AKI). However, this invasive approach can lead to morbidity, delayed glucocorticoid treatment for patients with AIN, and unnecessarily prolonged suspension of ICI therapy in non-AIN patients.
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