Pediatrics

Deep Learning Auto-segmentation of Diffuse Midline Glioma on Multimodal Magnetic Resonance Images.

Diffuse midline glioma (DMG) H3 K27M-altered is a rare pediatric brainstem cancer with poor prognosis. To advance the development of predictive models to gain a deeper understanding of DMG, there is a crucial need for seamlessly integrating automatic and highly accurate tumor segmentation techniques. There is only one method that tries to solve this task in this cancer; for that reason, this study...

Perinatal responsibility in a fragmented world: reflections from the 2024 international academy of perinatal medicine New York meeting.

This editorial introduces the Special Issue of the Journal of Perinatal Medicine dedicated to the 2024 New York meeting of the International Academy of Perinatal Medicine (IAPM). Held from June 27-29, the meeting brought together global leaders in perinatal health to discuss advances in prenatal care, equity in maternal and neonatal outcomes, professional ethics, and the role of emerging technolog...

A Bibliometric Review of Person-Centered Care Research 2010-2024.

: Person-centered care (PCC) has become a pivotal concept in healthcare. At present, no published studies have assessed the PCC field using bibliometr...

Can ChatGPT Counter Vaccine Hesitancy? An Evaluation of ChatGPT's Responses to Simulated Queries from the General Public.

Vaccines have eradicated deadly diseases, yet vaccine hesitancy persists, leading to reduced uptake. Some individuals, mistrustful of healthcare prov...

Leveraging pre-vaccination antibody titres across multiple influenza H3N2 variants to forecast the post-vaccination response.

BACKGROUND: Despite decades of research on the influenza virus, we still lack a predictive understanding of how vaccination reshapes each person's ant...

Optimizing MRI sequence classification performance: insights from domain shift analysis.

BACKGROUND: MRI sequence classification becomes challenging in multicenter studies due to variability in imaging protocols, leading to unreliable meta...

Drug repurposing to identify potential FDA-approved drugs targeting three main angiogenesis receptors through a deep learning framework.

Tumor cell survival depends on the presence of oxygen and nutrients provided by existing blood vessels, particularly when cancer is in its early stage...

SLC35A2 loss-of-function variants affect glycomic signatures, neuronal fate and network dynamics.

SLC35A2 encodes a UDP-galactose transporter essential for glycosylation of proteins and galactosylation of lipids and glycosaminoglycans. Germline gen...

A pediatric ECG database with disease diagnosis covering 11643 children.

Electrocardiogram (ECG) is a common non-invasive diagnostic tool for cardiovascular diseases. Adequate data is crucial in utilizing deep learning to a...

A dataset for quality evaluation of pelvic X-ray and diagnosis of developmental dysplasia of the hip.

Developmental Dysplasia of the Hip (DDH) stands as one of the preeminent hip disorders prevalent in pediatric orthopedics. Automated diagnostic instru...

Comment on Dalboni da Rocha et al. Artificial Intelligence for Neuroimaging in Pediatric Cancer. 2025, , 622.

As researchers actively working in the field of pediatric neuroimaging and artificial intelligence, we were pleased to see your recent review, Artific...

Reply to Keles et al. Comment on "Dalboni da Rocha et al. Artificial Intelligence for Neuroimaging in Pediatric Cancer. 2025, , 622".

We thank the readers for their thoughtful reading of our review, "Artificial Intelligence for Neuroimaging in Pediatric Cancer", and for their interes...

Novel bioparameters derived from bioimpedance measurements for accurate prediction of weight status in infant-juvenile individuals: A regression analysis.

In this study, a linear support vector machine regression model was used to explore the correlation between weight status and two novel bioparameters,...

Development and validation of a machine learning model for in-hospital mortality prediction in children under 5 years with heart failure.

BACKGROUND: Heart failure (HF) in children under five years of age carries a high risk of in-hospital mortality, yet existing pediatric risk assessmen...

Deep learning-based framework for Mycobacterium tuberculosis bacterial growth detection for antimicrobial susceptibility testing.

Tuberculosis (TB) kills more people annually than any other pathogen. Resistance is an ever-increasing global problem, not least because diagnostics r...

Sex-related differences and associated transcriptional signatures in the brain ventricular system and cerebrospinal fluid development in full-term neonates.

BACKGROUND: The cerebrospinal fluid (CSF) is known to serve as a unique environment for neurodevelopment, with specific proteins secreted by epithelia...

Improved estimation of forage nitrogen in alpine grassland by integrating Sentinel-2 and SIF data.

Nitrogen is an essential element for the growth and reproduction of vegetation in alpine grasslands and plays a vital role in determining the nutrient...

Unmet needs in autoimmune liver diseases.

Autoimmune hepatitis, primary biliary cholangitis, and primary sclerosing cholangitis are well-defined autoimmune liver diseases, the pathophysiology ...

Adaptive Machine Learning Framework enables Unprecedented Yield and Purity of Adeno-Associated Viral Vectors for Gene Therapy.

Adeno-associated viral (AAV) vectors for gene therapy are becoming integral to modern medicine, providing therapeutic options for diseases once deemed...

Novel Technologies in Preterm Birth Prediction: Current Advances and Ethical Challenges.

Preterm birth (PTB) remains a significant challenge in modern obstetric practice, posing considerable risks to maternal and neonatal health. Despite a...