Pediatrics

Association of Music Therapy and Physiologic Indices in the Pediatric Cardiac Intensive Care Unit: Insights from Machine Learning and High-fidelity Physiologic Data.

Comparative evaluation of multimodal large language models for diagnostic accuracy in pediatric electrocardiography: a prospective comparative diagnostic accuracy study.

UNLABELLED: We evaluated three multimodal LLMs, ChatGPT (GPT-5.2), Gemini 3, and Microsoft Copilot, in pediatric ECG interpretation, focusing on clinically significant abnormalities and emergency arrhythmias with likelihood ratios as primary outcome measures. This prospective comparative diagnostic accuracy study (STARD/STARD-AI) included 264 pediatric patients with 12-lead ECGs (November 2024-Nov...

Contemporary clinical incident analysis methods used within acute care settings: a scoping review.

OBJECTIVE: The objective of this review was to explore and synthesize the research on the use of contemporary incident analysis methods in acute care ...

Evaluating Patient and Professional Satisfaction and Documentation Time Reduction Through AI-Driven Automatic Clinical Note Generation in Primary Care: Proof-of-Concept Study.

BACKGROUND: The workload that stems from writing clinical histories is one of the main sources of stress and overload for primary care professionals, ...

Artificial Intelligence in Neurocritical Care : Multimodal Biosignal Analysis for Prognosis, Monitoring, and Future Pediatric Applications.

Neurocritical care relies on continuous assessment of neurological function and physiology under time pressure, yet bedside teams must interpret high-...

What factors influence patient participation in an artificial intelligence-based initiative to optimise referrals from primary to specialist haematology care? A multicentre retrospective observational study in four Spanish hospitals.

OBJECTIVES: Increasing demand for haematological specialist care makes the optimisation of referrals and outpatient workflow a priority. Automated pla...

An integrated model of financial socialization, technology, and financial capability in predicting financial well-being.

This study develops and empirically tests an integrated framework that explains how financial socialisation, technological factors, and financial capa...

Altered brain network topology in adolescents with major depressive disorder and bipolar disorder: A resting-state fMRI graph-theoretical and machine learning study.

BACKGROUND: Adolescents with major depressive disorder (MDD) and bipolar disorder (BD) share substantial clinical overlap and elevated suicide risk, y...

Integration of Systemic Immune-Inflammation Index and Lactate for diagnostic and early risk stratification in pediatric sepsis.

Severe COVID-19 in the Republic of Korea: Epidemiology, Risk Factors, Therapeutics, and Prognostic Models From Nationwide Data.

Severe coronavirus disease 2019 (COVID-19) has posed ongoing clinical and public health challenges worldwide, with Korea providing a unique perspectiv...

REM Sleep Abnormalities in Children With Autism Spectrum Disorder.

Sleep disturbances are common in children with autism spectrum disorder (ASD). However, the sleep pattern changes including rapid eye movement (REM) s...

Deep learning model for automated identification of ventrally positioned right hepatic artery in contrast-enhanced computed tomography of pediatric congenital biliary dilatation: development and clinical application.

BACKGROUND: Preoperative identification of a ventrally positioned right hepatic artery (vRHA) is critical in congenital biliary dilatation (CBD), as u...

Harnessing Large Language Models in Neonatal IVH: Exploring RAG Methodology for Prognostic Variable Discovery.

OBJECTIVE: To evaluate whether large language models (LLMs) can autonomously synthesize existing literature and accurately extract prognostic variable...

Artificial Intelligence Applications in COVID-19-Associated Coagulopathy: Lessons Learned.

Coronavirus disease 2019 (COVID-19)-associated coagulopathy (CAC) is a thromboinflammatory syndrome marked by endothelial injury, micro- and macrovasc...

Communication, compassion, and shared decision-making in allergy.

Shared decision-making (SDM) is a structured approach to clinical care that integrates the best available evidence, clinician expertise, and patient v...

Rapid assessment of pesticide toxicity in aquatic ecosystems using deep learning-based automatic duckweed counting method.

Pesticides are widely used in agriculture to control weeds, insects, and diseases that threaten crop yields. However, their extensive use raises conce...

Comprehensive Evaluation of ChatGPT's Diagnostic Accuracy on Image-based Ophthalmic Case Interpretations.

OBJECTIVE: To evaluate the diagnostic and treatment accuracy of Chat Generative Pre-trained Transformer (GPT-4.o) in ophthalmology, comparing performa...

Artificial intelligence-based prediction of fetal hypoxia: a multicenter model development and nationwide AI-human comparison.

BACKGROUND: Fetal hypoxia is a leading cause of neonatal morbidity and mortality. Cardiotocography (CTG) is widely used to predict fetal hypoxia durin...

Assessment of artificial intelligence-based control algorithms to be implemented in an affordable transradial myoelectric prosthesis.

This study assesses artificial intelligence-based control algorithms for a transradial myoelectric prosthesis. The analysis is supported by a dataset ...

A social media driven model for evaluating coupled flood damage and resilience at a fine scale.

With the increasing frequency of extreme rainfall events due to climate change, enhancing flood resilience has become a critical focus for urban resea...