OBJECTIVE: This study aimed to improve treatment effectiveness in childhood-onset systemic lupus erythematosus (cSLE) by developing machine learning algorithms integrated with pharmacokinetic parameters to predict individualized tacrolimus dosing for...
Ecotoxicology and environmental safety
Sep 1, 2025
BACKGROUND: Polycyclic aromatic hydrocarbons (PAHs), widely emitted through industrial processes and vehicular exhaust, are recognized environmental carcinogens. Although PAH exposure has been linked to various malignancies, the specific molecular me...
Ecotoxicology and environmental safety
Sep 1, 2025
Our aim is to evaluate the association of prenatal exposure to per- and polyfluoroalkyl substances (PFAS) with offspring blood pressure (BP); examine the moderating effect of children's age; and the mediating effects of inflammatory cytokines. Data o...
European journal of clinical pharmacology
Sep 1, 2025
PURPOSE: This study develops and compares population pharmacokinetics (PopPK) models and machine learning methods, including neural networks, to predict steady-state trough concentrations in pediatric patients and provide improved dosing recommendati...
OBJECTIVE: This study aimed to demonstrate the use of deep learning for automating caries detection using intraoral scan data from children and to evaluate diagnostic agreement between the models' predictions and dental practitioner assessments on 3D...
This study focuses on the binary classification of pediatric epilepsy seizure types as focal or generalized using Turkish electroencephalography (EEG) reports, leveraging natural language processing (NLP) and machine learning methodologies. A novel d...
BACKGROUND: Determining whether pediatric patients with low-grade gliomas (pLGGs) have tumor-related epilepsy (GAE) is a crucial aspect of preoperative evaluation. Therefore, we aim to propose an innovative, machine learning- and deep learning-based ...
UNLABELLED: Synthetic MRI (SyMRI) is a technique used to estimate tissue properties and generate multiple MR sequence contrasts from a single acquisition. However, image quality can be suboptimal.
PURPOSE: To investigate the usefulness of a machine learning (ML) model that can predict the natural course of childhood myopia in evaluation of the inhibitory effects of 0.125% atropine on the progression of childhood myopia.
Journal of experimental child psychology
Sep 1, 2025
Children tend to imitate inefficient behaviors containing causally irrelevant actions-they over-imitate. Out-group members' efficient demonstration cannot reduce children's over-imitation of in-group members, due to their interpretation of irrelevant...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.