Pediatrics

Toward accurate prediction of pediatric epidemic disease patient volume in the Chaoshan region: A deep learning framework.

Accurate prediction of pediatric epidemic infectious diseases is critical for effective prevention and personalized treatment. Herein, we developed a deep learning framework for the epidemiological characteristics of the Chaoshan region, using electronic health records data from 278,506 pediatric outpatient and emergency visits at the Second Affiliated Hospital of Shantou University Medical Colleg...

Artificial intelligence in preterm birth prediction: a narrative review of current approaches and clinical applicability.

Preterm birth remains the leading cause of neonatal morbidity and mortality worldwide, affecting approximately 13.4 million births annually. Despite advances in our understanding of risk factors, current clinical prediction methods have demonstrated limited accuracy in individual risk stratification. This narrative review examines the current landscape of artificial intelligence (AI) applications ...

AI-Powered Ambient Scribe Technology Experiences Among Emergency Physicians: Cross-Sectional, Mixed Methods Pilot Survey Study.

BACKGROUND: Health care organizations have started to implement artificial intelligence-powered ambient scribe technology in clinical documentation wo...

Digital Technologies That Support Meaningful Connections in Care Homes: Scoping Review.

BACKGROUND: Meaningful connections in which people feel valued, seen, and heard are essential for social health and well-being. However, individual, s...

Enabling digital multifactorial risk assessment in primary care: an umbrella review and recommendations for design and implementation.

OBJECTIVES: To develop recommendations to inform development and integration of predictive digital health and artificial intelligence tools in primary...

Development and multicenter validation of an explainable machine learning diagnostic criteria for pediatric abdominal sepsis.

Accurate identification of early pediatric abdominal sepsis (PAS) is essential to improving outcomes, yet most existing pediatric sepsis criteria and ...

Non-suicidal self-injury in middle school students: Influencing factors and a risk prediction model.

Non-suicidal self-injury (NSSI) is becoming increasingly prevalent and harmful among adolescents, yet its intrinsic mechanism and early identification...

Adolescents Experiencing Both Bullying and Childhood Trauma: Longitudinal Patterns, Psychosocial Networks, and Risk Prediction.

Adolescents who experience both bullying at school and maltreatment within families are at heightened risk for psychological harm, yet little is known...

Systematic Review of Studies Investigating Infant Feeding Difficulties: Focus on Machine Learning Applications.

INTRODUCTION: This study aims to systematically review studies using machine learning for infant feeding difficulties and identify the clinical applic...

AutoPET Challenge on Fully Automated Lesion Segmentation in Oncologic PET/CT Imaging, Part 2: Domain Generalization.

This article reports the results of the second iteration of the autoPET challenge on automated lesion segmentation in whole-body PET/CT, held in conju...

Rapid Diagnosis of Bacteremia in Febrile Pediatric Oncology Patients via Host-Response Infrared Spectroscopy of Blood and Machine Learning.

Bacteremia is a life-threatening complication and a leading cause of sepsis and septic shock in patients. Conventional diagnostic methods, such as blo...

AI in Childbirth and Emerging Alternatives to Traditional Fertility Treatments.

Artificial Intelligence (AI) is revolutionizing reproductive medicine by enhancing fertility treatments, childbirth monitoring, and postnatal care. AI...

Artificial Intelligence Length-of-Stay Forecasting and Pediatric Surgical Capacity.

IMPORTANCE: Hospitals are increasingly experiencing challenges with variable and unpredictable inpatient loads, including days with excessively high a...

Transformer-based multidimensional feature fusion for accurate prediction of lipid nanoparticles transfection efficiency.

RNA-based technologies have demonstrated significant potential for diverse applications, ranging from vaccination to gene editing. However, their wide...

Diagnostic and Technological Advances in Magnetic Resonance (Focusing on Imaging Technique and the Gadolinium-Based Contrast Media), Computed Tomography (Focusing on Photon Counting CT), and Ultrasound-State of the Art.

Magnetic resonance continues to evolve and advance as a critical imaging modality for disease diagnosis and monitoring. Hardware and software advances...

A Spatiotemporal Causal Model for Revealing Developmental Changes in Infants' Brain Effective Connectivity Networks During the First Year of Life.

OBJECTIVE: The infant's brain undergoes significant structural and physiological transformations during the first year of life. Although extensive res...

CHOROIDAL VASCULARITY INDEX, RETINAL VASCULARITY, AND HEMOGLOBIN LEVELS IN PEDIATRIC SICKLE CELL MACULOPATHY.

PURPOSE: To evaluate the choroidal vascularity index (CVI) in pediatric patients with sickle cell disease (SCD) and its associations with retinal thic...

Within-Day Variations in Infant Body Position Predict Caregiver Speech Input.

Infants' time spent in different body positions varies substantially within a day: lying supine on their backs, crawling or playing while prone on the...

SASBDB reaches 5000 data sets: empowering open science and next-generation SAS analysis.

The Small-Angle Scattering Biological Data Bank (SASBDB) has recently reached a milestone of 5000 entries, reflecting over a decade of community-drive...

[Cerebral neuromodulation in neurodevelopmental disorders].

Neurodevelopmental disorders comprise a heterogeneous group of conditions characterized by earlyonset impairments in cognitive, behavioral, emotional,...