Pediatrics

Prediction and characterisation of the human B cell response to a heterologous two-dose Ebola vaccine.

Ebola virus disease (EVD) outbreaks are increasing, posing significant threats to affected communities. Effective outbreak management depends on protecting frontline health workers, a key focus of EVD vaccination strategies. IgG specific to the viral glycoprotein serves as the correlate of protection for recent vaccine licensures. Using advanced cellular and transcriptomic analyses, we examined B ...

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 hormone (rhGH) therapy shows considerable variability. Predicting treatment outcomes is essential for optimizing individualized treatment strategies.

Clinical prediction of intravenous immunoglobulin-resistant Kawasaki disease based on interpretable Transformer model.

Intravenous immunoglobulin (IVIG) has been established as the first-line therapy for Kawasaki disease (KD). However, approximately 10%-20% of pediatri...

Predicting SARS-CoV-2-specific CD4 and CD8 T-cell responses elicited by inactivated vaccines in healthy adults using machine learning models.

The ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants highlights the importance of monitoring immune response...

Progress in the application research of cervical cancer screening developed by artificial intelligence in large populations.

Cervical cancer stands out among various cancers due to its potential for prevention and eradication, mainly through vaccination and proactive screeni...

Enhancing AI Readiness in Pediatric Surgery: Impact of a Targeted Workshop on Knowledge and Competencies.

INTRODUCTION: Despite an awareness of the transformative potential of Artificial Intelligence (AI) in healthcare, its development in pediatric surgery...

Implementing Artificial Intelligence in Critical Care Medicine: a consensus of 22.

Artificial Intelligence (AI) is rapidly transforming the landscape of critical care, offering opportunities for enhanced diagnostic precision and pers...

Bifunctional Phyto-Synthesized Nano Silver for Mitigating Salinity-Induced Dormancy and Associated Fungal Infections During Seed Germination in Brassica juncea with Integration of Machine Learning-Based Predictive Modeling.

Salinity-induced dormancy associated with fungal infection during germination in plants is the major contributor to abiotic and biotic stress, leading...

Harnessing technology for hope: a systematic review of digital suicide prevention tools.

This systematic review scrutinizes digital interventions in suicide prevention, telehealth, mobile applications, artificial intelligence (AI), and dig...

Current Research and Development in the Field of Magnetic Resonance Contrast Media.

The next-generation, high relaxivity, gadolinium-based contrast agents (GBCAs) are discussed, together with new studies of safety, improvements in MR ...

Reviving the Past, Moving on to the Present, and Planning for the Future of Craniofacial Malformations.

The malformed newborn with craniofacial anomalies was variously regarded in different civilizations. Some populations considered it a symbol of the pr...

Development and evaluation of machine learning training strategies for neonatal mortality prediction using multicountry data.

Neonatal mortality poses a critical challenge in global health, particularly in low- and middle-income countries. Leveraging advancements in technolog...

Autonomous screening of infants at high risk for neurodevelopmental impairments using a radar sensor and machine learning.

Neurodevelopmental impairments (NDIs) are significant long-term complications in preterm infants. While early recognition of infants at high risk for ...

The development of the generative adversarial supporting vector machine for molecular property generation.

The generative adversarial network (GAN) is a milestone technique in artificial intelligence, and it is widely used in image generation. However, it h...

Novel 59-layer dense inception network for robust deepfake identification.

The exponential growth of Artificial Intelligence (AI) has led to the emergence of cutting edge methods and a plethora of new tools for media editing....

Dual Functions and Therapeutic Potential of FZD6 in Biliary Atresia.

OBJECTIVE: Biliary atresia (BA), a severe neonatal cholangiopathy, lacks pharmacological therapies. This study aimed to identify causal genes and ther...

Identification of inflammation-related biomarkers and therapeutic targets for neurogenic bladder fibrosis via multi-omics analysis.

Inflammatory responses play a crucial role in the progression of pediatric neurogenic bladder (NB)-associated fibrosis; however, their specific contri...

Dosing prediction of valproic acid in pediatric patients with epilepsy: population pharmacokinetic model or machine learning model?

PURPOSE: This study develops and compares population pharmacokinetics (PopPK) models and machine learning methods, including neural networks, to predi...

Early transcriptional responses reveal cell type-specific vulnerability and neuroprotective mechanisms in the neonatal ischemic hippocampus.

Neonatal hypoxic-ischemic (H-I) brain injury, a leading cause of neurodevelopmental disabilities, severely affects the metabolically active and neurog...

Leveraging machine learning and single-cell RNA sequencing strategies to develop a risk prognosis scoring based on liquid-liquid phase separation feature genes in pediatric hepatoblastoma.

BACKGROUND: Considerable evidence highlights the intricate association between liquid-liquid phase separation (LLPS) and tumorigenesis, progression, a...