Pediatrics

Evaluating machine- and deep learning approaches for artifact detection in infant EEG: classifier performance, certainty, and training size effects.

Electroencephalography (EEG) is essential for studying infant brain activity but is highly susceptib...

Youth Perspectives on Generative AI and Its Use in Health Care.

A nationwide survey of youth aged 14 to 24 years on generative artificial intelligence (GAI) found t...

New level of evidence grading system for Guidelines, artificial intelligence, and adult congenital heart disease.

Evaluating Prevalence of Preterm Postnatal Growth Faltering Using Fenton 2013 and INTERGROWTH-21st Growth Charts with Logistic and Machine Learning Models.

Postnatal growth faltering (PGF) significantly affects premature neonates, leading to compromised n...

Development of a machine learning prediction model for loss to follow-up in HIV care using routine electronic medical records in a low-resource setting.

BACKGROUND: Despite the global commitment to ending AIDS by 2030, the loss of follow-up (LTFU) in HI...

Machine learning based clinical decision tool to predict acute kidney injury and survival in therapeutic hypothermia treated neonates.

Therapeutic hypothermia (TH) significantly reduces mortality and morbidities in neonates with Neonat...

Feasibility of machine learning-based modeling and prediction to assess osteosarcoma outcomes.

Osteosarcoma, an aggressive bone malignancy predominantly affecting children and adolescents, is cha...

Artificial intelligence in pediatric dental trauma: do artificial intelligence chatbots address parental concerns effectively?

BACKGROUND: This study focused on two Artificial Intelligence chatbots, ChatGPT 3.5 and Google Gemin...

Assessing fetal lung maturity: Integration of ultrasound radiomics and deep learning.

This study built a model to forecast the maturity of lungs by blending radiomics and deep learning m...

A novel framework for sentiment classification employing Bi-GRU optimized by enhanced human evolutionary optimization algorithm.

Sentiment analysis of content is highly essential for myriad natural language processing tasks. Part...

Metabolomics and machine learning identify urine metabolic characteristics and potential biomarkers for severe Mycoplasma pneumoniae pneumonia.

To study the differences in the urine metabolome between pediatric patients with severe Mycoplasma p...

A roadmap for safe, regulation-compliant Living Labs for AI and digital health development.

Safe and agile experimentation spaces are essential for developing AI-enabled medical devices and di...

Computer-aided assessment for enlarged fetal heart with deep learning model.

Enlarged fetal heart conditions may indicate congenital heart diseases or other complications, makin...

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

IMPORTANCE: Despite increasingly widespread use of artificial intelligence-driven ambient scribes in...

Private Data Incrementalization: Data-Centric Model Development for Clinical Liver Segmentation.

Machine Learning models, more specifically Artificial Neural Networks, are transforming medical imag...

Achieving SDoH Resource Equity in PICU Using an AI-Enabled Patient Navigator.

Trauma care coordination in the pediatric intensive care unit (PICU), including personalization of r...

Extracting Pediatric Information from Summaries of Product Characterics with a Large Language Model and No-Code.

Accurate medication information is important for children, as dosing errors can have severe conseque...

Utilizing Large Language Models to Monitor Social Media for Disability: An Analysis of Sentiment and Disability Models in Tweets.

This study explores how well large language models (like the kind that powers ChatGPT) can analyze o...

A Review of Challenges in Speech-Based Conversational AI for Elderly Care.

Artificially intelligent systems optimized for speech conversation are appearing at a fast pace. Suc...

Leveraging Large Language Models for Synthetic Data Generation to Enhance Adverse Drug Event Detection in Tweets.

Adverse drug event (ADE) detection in social media texts poses significant challenges due to the inf...

Exploring the Role of Digital Twins in Heart Care: Research Directions and Applications.

The concept of digital twins has emerged as a transformative innovation in healthcare. Digital twins...