AI Medical Compendium Journal:
Pediatrics

Showing 1 to 10 of 10 articles

Machine Learning for Accurate Intraoperative Pediatric Middle Ear Effusion Diagnosis.

Pediatrics
OBJECTIVES: Misdiagnosis of acute and chronic otitis media in children can result in significant consequences from either undertreatment or overtreatment. Our objective was to develop and train an artificial intelligence algorithm to accurately predi...

Machine Learning for Child and Adolescent Health: A Systematic Review.

Pediatrics
CONTEXT: In the last few decades, data acquisition and processing has seen tremendous amount of growth, thus sparking interest in machine learning (ML) within the health care system.

Large Language Models in Pediatric Education: Current Uses and Future Potential.

Pediatrics
Generative artificial intelligence, especially large language models (LLMs), has the potential to affect every level of pediatric education and training. Demonstrating speed and adaptability, LLMs can aid educators, trainees, and practicing pediatric...

Surveillance of Health Care-Associated Violence Using Natural Language Processing.

Pediatrics
BACKGROUND AND OBJECTIVES: Patient and family violent outbursts toward staff, caregivers, or through self-harm, have increased during the ongoing behavioral health crisis. These health care-associated violence (HAV) episodes are likely under-reported...

Single-Examination Risk Prediction of Severe Retinopathy of Prematurity.

Pediatrics
BACKGROUND AND OBJECTIVES: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness. Screening and treatment reduces this risk, but requires multiple examinations of infants, most of whom will not develop severe disease. Previous wo...

Creative Approaches for Assessing Long-term Outcomes in Children.

Pediatrics
Advances in new technologies, when incorporated into routine health screening, have tremendous promise to benefit children. The number of health screening tests, many of which have been developed with machine learning or genomics, has exploded. To as...

Applications of Artificial Intelligence for Retinopathy of Prematurity Screening.

Pediatrics
OBJECTIVES: Childhood blindness from retinopathy of prematurity (ROP) is increasing as a result of improvements in neonatal care worldwide. We evaluate the effectiveness of artificial intelligence (AI)-based screening in an Indian ROP telemedicine pr...

Machine Learning To Predict Serious Bacterial Infections in Young Febrile Infants.

Pediatrics
BACKGROUND: Recent decision rules for the management of febrile infants support the identification of infants at higher risk of serious bacterial infections (SBIs) without the performance of routine lumbar puncture. We derive and validate a model to ...

Social Robots for Hospitalized Children.

Pediatrics
BACKGROUND AND OBJECTIVES: Social robots (SRs) are increasingly present in medical and educational contexts, but their use in inpatient pediatric settings has not been demonstrated in studies. In this study, we aimed to (1) describe the introduction ...