Pediatrics

Artificial intelligence-based, non-invasive assessment of the central aortic pressure in adults after operative or interventional treatment of aortic coarctation.

BACKGROUND: Aortic coarctation (CoA) is a congenital anomaly leading to upper-body hypertension and lower-body hypotension. Despite surgical or interventional treatment, arterial hypertension may develop and contribute to morbidity and mortality. Conventional blood pressure (BP) measurement methods lack precision for individual diagnoses and therapeutic decisions. This study evaluated the use of a...

Interpreting IGF-1 in children treated with recombinant growth hormone: challenges during early puberty.

OBJECTIVE: It can be challenging to determine the correct dosage of recombinant growth hormone (GH) in children with GH deficiency, leading to highly variable treatment responses. Insulin-like growth factor-1 (IGF-1) is a tool for monitoring GH treatment and dosing. However, IGF-1 levels depend on sex, age, and pubertal stage, amongst other factors, making its interpretation somewhat difficult. Th...

Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat ( L.).

Phytochromes are essential photoreceptors in plants that sense red and far-red light, playing a vital role in regulating plant growth and development ...

Psychological and Behavioral Insights From Social Media Users: Natural Language Processing-Based Quantitative Study on Mental Well-Being.

BACKGROUND: Depression significantly impacts an individual's thoughts, emotions, behaviors, and moods; this prevalent mental health condition affects ...

Cell clone selection-impact of operation modes and medium exchange strategies on clone ranking.

Bioprocessing has been transitioning from batch to continuous processes. As a result, a considerable amount of resource was dedicated to optimising st...

Predicting fall parameters from infant skull fractures using machine learning.

When infants are admitted to the hospital with skull fractures, providers must distinguish between cases of accidental and abusive head trauma. Limite...

Claude, ChatGPT, Copilot, and Gemini performance versus students in different topics of neuroscience.

Despite extensive studies on large language models and their capability to respond to questions from various licensed exams, there has been limited fo...

Convolutional neural network (CNN) configuration using a learning automaton model for neonatal brain image segmentation.

CNN is considered an efficient tool in brain image segmentation. However, neonatal brain images require specific methods due to their nature and struc...

Artificial Intelligence-Powered Human Epidermal Growth Factor Receptor 2 and Tumor Microenvironment Analysis in Human Epidermal Growth Factor Receptor 2-Amplified Metastatic Colorectal Cancer: Exploratory Analysis of Phase II TRIUMPH Trial.

PURPOSE: Human epidermal growth factor receptor 2 (HER2)-targeted therapies have shown promise in treating -amplified metastatic colorectal cancer (mC...

Method for assessing visual saliency in children with cerebral/cortical visual impairment using generative artificial intelligence.

Cerebral/cortical visual impairment (CVI) is a leading cause of pediatric visual impairment in the United States and other developed countries, and is...

Applications of Machine Learning Approaches for the Discovery of SARS-CoV-2 PLpro Inhibitors.

The global impact of SARS-CoV-2 highlights the need for treatments beyond vaccination, given the limited availability of effective medications. While ...

A comparison of the persuasiveness of human and ChatGPT generated pro-vaccine messages for HPV.

INTRODUCTION: Public health messaging is crucial for promoting beneficial health outcomes, and the latest advancements in artificial intelligence offe...

A machine learning-based analysis for the effectiveness of online teaching and learning in Pakistan during COVID-19 lockdown.

BackgroundThe COVID-19 pandemic has significantly disrupted daily life and education, prompting institutions to adopt online teaching.ObjectiveThis st...

Precision fetal cardiology detects cyanotic congenital heart disease using maternal saliva metabolome and artificial intelligence.

Prenatal sonographic diagnosis of congenital heart disease (CHD) can lead to improved morbidity and mortality. However, the diagnostic accuracy of ult...

Derivation and validation of a clinical predictive model for longer duration diarrhea among pediatric patients in Kenya using machine learning algorithms.

BACKGROUND: Despite the adverse health outcomes associated with longer duration diarrhea (LDD), there are currently no clinical decision tools for tim...

Clinical validation of explainable AI for fetal growth scans through multi-level, cross-institutional prospective end-user evaluation.

We aimed to develop and evaluate Explainable Artificial Intelligence (XAI) for fetal ultrasound using actionable concepts as feedback to end-users, us...

An Efficient Acute Lymphoblastic Leukemia Screen Framework Based on Multi-Modal Deep Neural Network.

BACKGROUND: Acute lymphoblastic leukemia (ALL) is a leading cause of death among pediatric malignancies. Early diagnosis of ALL is crucial for minimiz...

Deep learning-based assessment of missense variants in the gene presented with bilateral congenital cataract.

OBJECTIVE: We compared the protein structure and pathogenicity of clinically relevant variants of the gene with AlphaFold2 (AF2), Alpha Missense (AM)...

Machine-learning-assisted Preoperative Prediction of Pediatric Appendicitis Severity.

PURPOSE: This study evaluates the effectiveness of machine learning (ML) algorithms for improving the preoperative diagnosis of acute appendicitis in ...

Development of immune-derived molecular markers for preeclampsia based on multiple machine learning algorithms.

Preeclampsia (PE) is a major pregnancy-specific cardiovascular complication posing latent life-threatening risks to mothers and neonates. The contribu...