Pediatrics

Latest AI and machine learning research in pediatrics for healthcare professionals.

7,324 articles
Stay Ahead - Weekly Pediatrics research updates
Subscribe
Browse Categories
Showing 5521-5540 of 7,324 articles

From Research to Impact: Assessing a Decade of CDC’s Public Health Science by Topic Area, 2014-2023

This study provides an objective, in-depth overview of a large body of science output addressing public health. We apply topic modeling and bibliometric tools to explore the relevance and impact of a decade of CDC-authored publications. We identified 34,104 scientific publications from 2014-2023 with ≥1 CDC-affiliated author using Science Clips, a CDC library database. We applied a large language ...

Screening for anemia using multi-modal machine learning models on smartphones: protocol for a comparative accuracy study in rural India

Anemia, or low blood hemoglobin (Hb), affects one third of the world population, and is particularly prevalent in women and children in lower resource settings. However, screening for anemia is limited by the availability of accurate, easy to use, lower cost and non-invasive methods. We aim to generate research to support potential development of a point of care test to detect anemia using smartph...

Deep-learning Segmentation of Pediatric Brain Tumors using Ratio Maps of T1w/T2w MRI Signal Intensity

T1w/T2w ratio mapping, combining voxel-wise signal intensities in T1-weighted (T1w) and T2-weighted (T2w) structural MRI, has been used to investigate...

PanEcho: Complete AI-enabled echocardiography interpretation with multi-task deep learning

Echocardiography is a cornerstone of cardiovascular care but relies on expert interpretation and manual reporting from a series of videos. We propose ...

The use of Artificial Intelligence in the out of hospital care settings: A Scoping Review

Out of hospital services face significant challenges, including growing patient demand, workforce limitations, and evolving care pathways. Artificial ...

Association of Deep Learning-Derived Histologic Features of Placental Chorionic Villi with Maternal and Infant Characteristics in the New Hampshire Birth Cohort Study

Quantification of placental histopathological structures is challenging due to a limited number of perinatal pathologists, constrained resources, and ...

The gSOS Polygenic Score is Associated with Bone Density and Fracture Risk in Childhood

The polygenic risk score genetic quantitative ultrasound speed of sound (gSOS) was developed using machine learning algorithms in adults of European a...

Machine Learning Improves the Predictive Utility of Lactic Acid in Hospitalized Infants

Hyperlactatemia is common in hospitalized infants. Machine learning was applied to clinical and laboratory characteristics in hospitalized infants wit...

AI vs. Traditional ultrasound study in Congenital Heart Defect Detection: A Systematic review

Prenatal detection rates for CHD have increased with improved ultrasound technology and imaging, the use of the first trimester fetal echocardiography...

Analyzing the Capacity of ChatGPT and Google to Provide Medical Information: Insights from Umbilical Cord Clamping

The optimal timing of umbilical cord clamping in neonatal care has been a subject of debate for decades. Recently, artificial intelligence (AI) has em...

A simple feed forward neural network to predict the 2025 outbreak of measles in the USA

Measles is a highly contagious viral disease associated with a variety of severe complications. Since 1963, widespread usage of a highly effective vac...

Understanding the Feasibility of Computer Vision in Diagnosing Respiratory Infections in Pediatric Emergency Rooms

Respiratory infections are a leading cause of pediatric emergency visits globally, requiring timely and accurate assessment. This study evaluated the ...

ARE LLMS READY FOR PEDIATRICS? A COMPARATIVE EVALUATION OF MODEL ACCURACY ACROSS CLINICAL DOMAINS

Large Language Models (LLMs) are rapidly emerging as promising tools in the healthcare field, yet their effectiveness in pediatric contexts remains un...

Feasibility of Machine Learning Analysis for the Identification of Patients with Possible Primary Ciliary Dyskinesia

Significant diagnostic delays are common in primary ciliary dyskinesia (PCD), a rare disease that is significantly underdiagnosed. Scalable screening ...

Evaluation of Machine Learning Models for Early Prediction of Gestational Diabetes Using Retrospective Electronic Health Records from Current and Previous Pregnancies

To assess the performance of machine learning (ML) models in predicting gestational diabetes mellitus (GDM) using electronic health record (EHR) data ...

ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL METHODS FOR MODELLING AND FORECASTING INFLUENZA AND INFLUENZA-LIKE ILLNESS: A SCOPING REVIEW

The persistnt resurgence of influence and influenza-like illness despite concerted vaccination interventions is a global health burden, thus necessita...

PED-X-Bench: A Benchmark of Adult-to-Pediatric Extrapolation Decisions in FDA Drug Labels

Pediatric trials are ethically and logistically difficult, so the U.S. FDA often extrapolates adult data to children when justified. Yet no public res...

Changes in psychiatric documentation and treatment in primary care with artificial intelligence scribe use

Despite increasingly widespread use of artificial intelligence-driven ambient scribes in medicine, the extent to which they may impact clinician pract...

Artificial Intelligence in Outpatient Primary Care: A Scoping Review on Applications, Challenges, and Future Directions

Artificial intelligence (AI) has the potential to revolutionize clinical decision-making and significantly improve patient outcomes in outpatient prim...

Advances in Newborn Screening for Sickle Cell Disease: A Systematic Review of Diagnostic Methods and Innovations

Sickle cell disease (SCD) is one of the most prevalent hemoglobinopathies worldwide, particularly in regions with high genetic predisposition. Early d...

Browse Categories