Pediatrics

Positron emission tomography imaging of inflammation and infection in children: an update.

Positron emission tomography (PET) has been used in pediatric oncology since the modality gained traction 20 years ago but has been used more sparingly in infectious and inflammatory diseases due to the ionizing radiation involved. However, more recent PET/CT systems allowing for the reduction of radiation dose have resulted in markedly more referrals, for these indications, over the past decade. ...

De-risking Biopharma Asset Acquisition: Towards a Quantitative Framework for Strategic Decision-making.

The impending patent cliff projected between 2028-2030 poses significant commercial and strategic challenges for innovative pharmaceutical and biotechnology companies. To sustain growth and maintain competitive positioning, organizations are increasingly relying on strategic mergers, acquisitions, and partnerships to replenish pipelines. However, systematic quantitative strategies and framework fo...

Automated detection of pediatric forearm fractures in X-ray images using deep learning.

Children's bones are more elastic and have a thicker periosteum than those of adults, resulting in subtle, incomplete fractures. Diagnosis based on pl...

Multimodal deep learning prediction of treatment response to anti-vascular endothelial growth factor in diabetic macular oedema.

OBJECTIVE: To develop and validate a multimodal deep learning model that predicts treatment responses to intravitreal anti-vascular endothelial growth...

Research progress on biomarkers for acute kidney injury in children.

Pediatric acute kidney injury (AKI) often presents insidiously and progresses rapidly. Traditional diagnostic criteria based on serum creatinine and u...

Applying Machine Learning to Fetal Echocardiograms: A Novel Method for Predicting Critical Coarctation of the Aorta.

BACKGROUND: Current fetal echocardiographic metrics are inadequate for confident prediction of neonatal critical coarctation of the aorta due to low s...

Examination of Pathologist-Artificial Intelligence Interactions and Their Impact on Pathologist Accuracy Using Artificial Intelligence-Assisted Scoring of Immunohistochemistry for Human Epidermal Growth Factor Receptor 2.

CONTEXT.—: Advances in computer vision have fueled the development of artificial intelligence (AI)-based algorithms for pathology. AI-assisted approac...

Diuretic Ultrasound Evaluation of Surgical Necessity in Pediatric Ureteropelvic Junction Obstruction.

RATIONALE AND OBJECTIVES: This study aimed to develop an interpretable machine learning (ML) model using diuretic ultrasonography to predict the neces...

Recent Advances in Hypothalamic Segmentation for Neuroimaging: A Comprehensive Review.

The hypothalamus is a key structure in the human brain, comprising numerous functionally distinct subnuclei that regulate critical physiological proce...

Artificial intelligence in nutritional assessment and decision making.

PURPOSE OF THE REVIEW: Artificial intelligence (AI) has become an non contourable tool in clinical nutrition practice. This review proposes to discuss...

Machine learning approaches in predicting circadian rhythm sleep-wake disorders: A review.

Circadian rhythm sleep-wake disorders (CRSWDs) arise from misalignment between an individual's sleep-wake timing and endogenous circadian physiology, ...

Automatic Detection of Ganglion Cells as a Supporting Tool for Hirschsprung Disease Diagnosis.

Hirschsprung disease (HD) is a congenital disorder characterized by the absence of ganglion cells in the colonic nervous plexuses, resulting in bowel ...

Global Sentiment Toward Health AI at the Dawn of the ChatGPT Era: Empirical Analysis of Twitter (X) Discourse.

BACKGROUND: Artificial intelligence (AI) is increasingly proposed for use in health and health care systems. Beyond technical performance, public perc...

Empathy in AI for Health and Care Settings-Definition, Expression, and Measurement: Protocol for a Scoping Review.

BACKGROUND: "Empathy" is widely discussed in health and care settings and is increasingly claimed as an attribute of artificial intelligence (AI) syst...

Identifying factors associated with vaping cessation in young adults: A machine learning and XAI approach.

The public health impact of vaping in the United States reflects a complex balance of potential benefits and emerging risks, as e‑cigarettes may reduc...

Towards Social Good: How Can Social Media Inform the Next GenAI's Collaboration With Humans for Dietary Support?

The rapid advancement of Generative AI (GenAI) has transformed human-computer interaction, particularly in domains requiring personalized guidance, su...

Surgical and hormonal gender-affirming care: cross-domain determinants and artificial intelligence-enabled expansion.

Gender-affirming surgery (GAS) and gender-affirming hormone therapy (GAHT) and are evidence-based components of care that support the health and well-...

Multi-omics-based machine learning model predicts response and guides treatment in Crohn disease: a case study in nutritional therapy.

BACKGROUND: Biomarkers are needed to predict treatment response and guide therapeutic decisions in Crohn disease (CD). We aimed to develop and validat...

Risks and Harms of Conversational Artificial Intelligence (CAI) Chatbot Use Among US Youth.

INTRODUCTION: Conversational AI (CAI) chatbots are widely used by adolescents for instruction, entertainment, companionship, and advice, but concerns ...

Getting ahead of sudden cardiac arrest in pediatric hypertrophic cardiomyopathy patients.

INTRODUCTION: Sudden cardiac arrest (SCA) remains one of the most devastating complications of pediatric hypertrophic cardiomyopathy (HCM). Despite ma...