Pediatrics

Prediction of suicidal attempts among Chinese adolescents with mood disorders: a clinical study using a machine learning approach.

Integrating vision transformer-based deep learning model with kernel extreme learning machine for non-invasive diagnosis of neonatal jaundice using biomedical images.

Birth complications, particularly jaundice, are one of the leading causes of adolescent death and di...

OR-FCOS: an enhanced fully convolutional one-stage approach for growth stage identification of Oudemansiella raphanipes.

Accurate identification of Oudemansiella raphanipes growth stages is crucial for understanding its d...

Utilizing CBNet to effectively address and combat cyberbullying among university students on social media platforms.

Cyberbullying can profoundly impact individuals' mental health, leading to increased feelings of anx...

Development and Validation of a Large Language Model-Powered Chatbot for Neurosurgery: Mixed Methods Study on Enhancing Perioperative Patient Education.

BACKGROUND: Perioperative education is crucial for optimizing outcomes in neuroendovascular procedur...

Artificial Intelligence Enhances Diagnostic Accuracy of Contrast Enemas in Hirschsprung Disease Compared to Clinical Experts.

Contrast enema (CE) is widely used in the evaluation of suspected Hirschsprung disease (HD). Deep le...

AI-driven robotic surgery in oncology: advancing precision, personalization, and patient outcomes.

Artificial intelligence (AI) integrated with robotic systems is transforming oncologic surgery by si...

Accelerated brain magnetic resonance imaging with deep learning reconstruction: a comparative study on image quality in pediatric neuroimaging.

BACKGROUND: Magnetic resonance imaging (MRI) is crucial in pediatric radiology; however, the prolong...

Management of mandibular infantile desmoid fibromatosis: A pediatric case report.

INTRODUCTION: Infantile desmoid fibromatosis (IDF) is a rare, benign soft tissue tumor, with locally...

Implementing Large Language Models in Health Care: Clinician-Focused Review With Interactive Guideline.

BACKGROUND: Large language models (LLMs) can generate outputs understandable by humans, such as answ...

Dental age estimation by comparing Demirjian's method and machine learning in Southeast Brazilian youth.

This study evaluated the applicability of combining Demirjian's method with machine learning algorit...

A novel artificial Intelligence-Based model for automated Lenke classification in adolescent idiopathic scoliosis.

PURPOSE: To develop an artificial intelligence (AI)-driven model for automatic Lenke classification ...

Artificial Intelligence Performance in Pediatric Asthma.

OBJECTIVE: Asthma is the most common chronic disease of childhood, characterized by symptoms such as...

Short-horizon neonatal seizure prediction using EEG-based deep learning.

Strategies to predict neonatal seizure risk have typically focused on long-term static predictions w...

Modelling key ecological factors influencing the distribution and content of silymarin antioxidant in Silybum marianum L.

The increasing demand for natural medicine has increased the significance of Silybum marianum as a v...

PediMS: A Pediatric Multiple Sclerosis Lesion Segmentation Dataset.

Multiple Sclerosis (MS) is a chronic autoimmune disease that primarily affects the central nervous s...

Deep learning to assess erythritol in zebrafish development, circadian rhythm, and cardiovascular disease risk.

Erythritol is one of the most widely used artificial sweeteners, yet the potential risks remain a su...

Genome sequencing is critical for forecasting outcomes following congenital cardiac surgery.

While exome and whole genome sequencing have transformed medicine by elucidating the genetic underpi...

Conversational Systems for Social Care in Older Adults: Protocol for a Scoping Review.

BACKGROUND: Social care systems worldwide face increasing demographic and financial pressures. This ...

Quo vadis neonatologia? Where is neonatology heading in the 21st century?

INTRODUCTION: This comprehensive narrative review examines current paradigms, emerging trends, and f...

Construction and evaluation of a height prediction model for children with growth disorders treated with recombinant human growth hormone.

BACKGROUND: Height gain in children with growth disorders undergoing recombinant human growth hormon...