Latest AI and machine learning research in pediatrics for healthcare professionals.
Artificial intelligence (AI) has the potential to revolutionize critical care medicine by enhancing patient care, improving resource allocation and reducing clinician workload. Despite this promise, many AI applications remain confined to scientific research rather than being integrated into everyday clinical practice. This manuscript aims to help intensivists prepare themselves and their intensiv...
Ocular blood flow imaging techniques have become indispensable in current clinical practice because retinal vascular disturbances have been implicated in the pathophysiology of numerous ocular diseases. In this review, we explore the applications of laser Doppler flowmetry, laser speckle flowgraphy (LSFG), and optical coherence tomography angiography (OCTA), focusing on LSFG and OCTA. Each modalit...
PURPOSE: In the post-COVID era, recognizing evolving physician competencies is crucial for guiding medical education and test development. This study ...
BACKGROUND: Tele-ophthalmology is transforming eye care delivery, particularly in remote and underserved areas, where specialist shortages and geograp...
Traditionally, CT has been the go-to method for visualizing bone structures, while MRI has been preferred for assessing soft tissues, because structur...
There is considerable evidence implicating maternal immune activation (MIA) and cytokine dysregulation in the pathophysiology of Autism. However, cyto...
Objective: This study aimed to evaluate and compare the accuracy, clarity, and clinical applicability of 2 state-of-the-art large language models (LLM...
BACKGROUND: Despite widespread use of intrapartum fetal monitoring, rates of fetal brain injury remain unchanged. Neonatal encephalopathy due to hypox...
Artificial intelligence (AI) is rapidly emerging as a transformative force in pediatric nephrology, enabling improvements in diagnostic accuracy, ther...
OBJECTIVES: To evaluate the performance of artificial intelligence (AI)-based models in predicting elevated neonatal insulin levels through fetal hepa...
This study aimed to develop an AI-based diagnostic model for Hirschsprung's disease (HD) using deep learning on contrast enema (CE) images, with the g...
Increases in impulsivity and negative affect (e.g., neuroticism) are common during adolescence and are both associated with risk for alcohol-use initi...
BACKGROUND: Chatbots are increasingly utilized in the health care landscape, including in sexual and reproductive health (SRH). These tools have shown...
This study evaluates Chat Generative Pre-Trained Transformer 4o's (ChatGPT-4o's) utility in clinical relevance and accuracy compared with Google for p...
BACKGROUND CONTEXT: Spinal low-grade gliomas (SLGGs) are rare, slow-growing central nervous system tumors affecting both pediatric and adult populatio...
One of the most ubiquitous and profound impacts to the delivery of healthcare over the last three decades has been the introduction of digital technol...
Artificial intelligence (AI) and machine learning (ML) models rapidly transform health care with applications ranging from diagnostic image interpreta...
BACKGROUND: Artificial intelligence (AI) applications for pediatric fracture diagnosis using radiographs have demonstrated growing potential in clinic...
BACKGROUND: Although recent advancements in artificial intelligence (AI) provide an alternative for infant motor assessment, such applications focus m...
BACKGROUND: Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are severe mucocutaneous reactions primarily triggered by drugs or inf...