Pediatrics

Artificial Intelligence's Role in Improving Adverse Pregnancy Outcomes: A Scoping Review and Consideration of Ethical Issues.

: Adverse pregnancy outcomes (APOs), which include hypertensive disorders of pregnancy (gestational hypertension, preeclampsia, and related disorders), gestational diabetes, preterm birth, fetal growth restriction, low birth weight, small-for-gestational-age newborn, placental abruption, and stillbirth, are health risks for pregnant women that can have fatal outcomes. This study's aim is to invest...

Tract integrity predicts neurological outcomes in neonatal hypoxic-ischemic encephalopathy.

OBJECTIVE: Early prognostication in infants with neonatal hypoxic-ischemic encephalopathy (HIE) is crucial for follow-up management. Alternations of microstructural integrity of neural fiber tracts in large-scale neural networks might predict neurological outcomes.

Machine Learning-Based Prediction of Post-Operative Systemic Inflammatory Response Syndrome Following Pediatric Percutaneous Nephrolithotripsy.

OBJECTIVE: This study aimed to develop and validate a machine learning-based model for predicting systemic inflammatory response syndrome (SIRS) in pe...

A qualitative analysis of college students' interest in mHealth solutions.

This study explores college students' perceptions of an AI-driven mHealth application designed to promote well-being. With rising mental health challe...

Physical and mental health management for the older adult using XGBoost algorithm supported by new media technology: developing personalized health intervention plans using healthcare data from the CLHLS database.

INTRODUCTION: With the increasing aging population, there is a growing need for precise and intelligent health management solutions tailored to older ...

Early diagnosis of autism across developmental stages through scalable and interpretable ensemble model.

Autism Spectrum Disorder (ASD) is a multifaceted neurodevelopmental condition that challenges early diagnosis due to its diverse manifestations across...

Leveling Up: Harnessing Cutting-Edge Technology to Enhance Oncology Education and Learning.

The integration and utilization of digital media, gamified learning strategies, and artificial intelligence (AI) are fundamentally transforming the la...

A Novel and Modern Calculator to Predict Vaginal Birth after Cesarean Delivery.

Counseling patients who are considering a trial of labor after cesarean (TOLAC) is a challenging task given the risks and benefits of either approach....

Predicting abnormal fetal growth using deep learning.

Ultrasound assessment of fetal size and growth is the mainstay of monitoring fetal well-being during pregnancy, as being small for gestational age (SG...

The Innovation Paradox in Emerging Pharmaceutical Markets: Barriers and Opportunities for Sustainable Development.

Emerging pharmaceutical markets like Brazil, India, and China have seen significant growth due to rising medication demand, expanding middle-class acc...

Development of a machine learning-based predictive nomogram for screening children with juvenile idiopathic arthritis: a pseudo-longitudinal study of 223,195 children in the United States.

BACKGROUND: Juvenile idiopathic arthritis (JIA) is a prevalent chronic rheumatological condition in children, with reported prevalence ranging from 12...

Applying exposure-response analysis to enhance Mycophenolate Mofetil dosing precision in pediatric patients with immune-mediated renal diseases by machine learning models.

BACKGROUND: Mycophenolate mofetil (MMF), a cornerstone immunosuppressant for lupus nephritis, is increasingly used off-label in pediatric immune-media...

Multimodal Machine Learning Analysis of GaSe Molecular Beam Epitaxy Growth Conditions.

Autonomous synthesis platforms integrating machine learning with in situ diagnostics have the potential to revolutionize thin-film growth by enabling ...

Comparative Evaluation of ChatGPT and ChatGLM Performance in Response to Common Queries on Pediatric Atopic Dermatitis.

BACKGROUND: Atopic dermatitis (AD) is a prevalent chronic and recurrent skin condition in children. Developing novel and standardized management strat...

Spatiotemporal Interrogation of Single Spheroids Using Multiplexed Nanoplasmonic-Fluorescence Imaging.

Advances in organoid models, as ex vivo mini-organs, and the development of screening imaging technologies have continuously driven each other forward...

Physics-based inverse modeling of battery degradation with Bayesian methods.

To further improve Lithium-ion batteries (LiBs), a profound understanding of complex battery processes is crucial. Physical models offer understanding...

Artificial intelligence in pediatric intensive care: unlocking integrated monitoring for autonomic nervous system dysregulation.

as a favorable prognostic biomarker in pediatric osteosarcoma: an integrated analysis of machine learning, bioinformatics, and validation experiments.

BACKGROUND: Osteosarcoma (OS), the most common pediatric bone tumor, faces challenges with frequent relapse despite treatment advances. Identifying ea...

Future Perspectives of Liver Research in the Asia-Pacific Region: Focus on Hepatitis B and C.

The Asia-Pacific region faces serious liver health challenges, primarily because of the comparatively high prevalence of hepatitis B virus (HBV) and h...

Comparison of ChatGPT-4, Microsoft Copilot, and Google Gemini for Pediatric Ophthalmology Questions.

PURPOSE: To evaluate the success of Chat Generative Pre-trained Transformer (ChatGPT; OpenAl), Google Gemini (Alphabet, Inc), and Microsoft Copilot (M...