Pediatrics

Video-based gait analysis for clinical monitoring of genotype-specific functional patterns in osteogenesis imperfecta.

BACKGROUND: Osteogenesis imperfecta (OI) is characterized by substantial genetic and functional heterogeneity, yet low-burden objective tools for repeated gait monitoring in routine outpatient care remain limited. This study investigated whether routine smartphone videos combined with markerless pose estimation could capture genotype-associated gait patterns in children with IFITM5- and WNT1-relat...

Predicting poor health-related quality of life among Chinese adolescents using explainable machine learning: the role of school adjustment, family context, and lifestyle factors.

BACKGROUND: Adolescents' health-related quality of life (HRQoL) is influenced by multiple domains, including school, family, and individual lifestyle. However, evidence remains limited on accurately predicting adolescent HRQoL and identifying modifiable determinants. This study aimed to develop a machine-learning prediction model for adolescent HRQoL and to determine key contextual factors associa...

Network and machine learning analysis of childhood trauma, mental health, and AI-based emotional support needs in adolescents from underdeveloped regions.

BACKGROUND: The current intervention efficacy of generative conversational artificial intelligence (GCAI) on overall mental health issues remains limi...

An expert-led benchmark using common patient questions: evaluating large language models for adolescent idiopathic scoliosis education.

AIM/BACKGROUND: Large language models (LLMs) are increasingly used by patients to obtain medical information. Adolescent idiopathic scoliosis (AIS), a...

Caregiver Preferences for AI-Supported Telemedicine in Pediatric Palliative Care: A Discrete Choice Experiment.

BackgroundAsynchronous telemedicine may support home-based pediatric palliative care (PPC) by improving access to professional guidance and reducing c...

Comparison of the performance of ChatGPT Plus, Gemini Pro, and experienced nurses in pediatric emergency triage using physician reference assessment: A prospective observational study.

AIM: We aimed to evaluate the performance of ChatGPT Plus and Gemini Pro, two large language model-based artificial intelligence (AI) tools, to predic...

Hetairos is a histology-based artificial intelligence model for predicting central nervous system tumor methylation subtypes.

Molecular testing is essential for classifying central nervous system (CNS) tumors, with methylation profiling providing the highest diagnostic granul...

Noninvasive PPROM risk stratification with explainable AI using routine antenatal CRP and albumin.

Premature rupture of membranes (PROM) and preterm PROM (PPROM) are significant obstetric complications, affecting 10-20% and 3% of pregnancies globall...

Artificial intelligence in sleep diagnostics for children under 2 years of age: state of the evidence and future directions.

BACKGROUND: Artificial intelligence (AI) has advanced rapidly in adult sleep medicine, but its role in children under 2 years old remains unclear. Thi...

Gauging support for autonomous delivery drones powered by artificial intelligence: A public survey in Singapore.

There has been emerging empirical evidence supporting the role of artificial intelligence (AI) knowledge in public support for AI. These findings stan...

The Future of Glaucoma: Data, Artificial Intelligence, and Precision Medicine for Patient-Centered Care.

PURPOSE: To summarize the main topics discussed during the 29th Annual Optic Nerve Rescue and Restoration Think Tank Meeting "The Future of Glaucoma: ...

ALADIN (Acne Lesion And Density INdex): a novel tool for automatic acne severity assessment.

BACKGROUND: Acne affects approximately 80% of adolescents worldwide, regardless of age, sex or ethnicity. Effective treatment depends on timely and ac...

Predicting Harm: A Systematic Review of Pediatric Pressure Injury Models and Their Clinical Shortcomings.

SIGNIFICANCE: Pediatric pressure injuries (PIs) are a distinct and preventable clinical challenge, yet risk prediction models tailored to children rem...

Artificial intelligence in pediatric intensive care units: current applications in sepsis management.

BACKGROUND: Early detection of sepsis in pediatric intensive care units (PICUs) is critical, but challenging due to its nonspecific clinical presentat...

Wave-aware mortality prediction in COVID-19: a multi-stage feature selection and explainable machine-learning framework.

BACKGROUND: Mortality among hospitalized COVID-19 patients changed markedly across successive epidemic waves as circulating variants shifted, populati...

Redesigning trauma-focused interventions to address capacity challenges in mental health systems.

Despite strong evidence supporting the use of trauma-focused evidence-based psychotherapies (EBPs) to treat posttraumatic stress disorder (PTSD), heal...

Evolution of Chatbots as an Educational and Supportive Digital Intervention for Family Caregivers of People With Dementia: Protocol for a Systematic Integrative Review.

BACKGROUND: Most people with dementia reside in the community and are cared for by family members. Family caregivers play an essential role in support...

Predictors of Detectable Viral Load among Adolescents with HIV in Low Resource Settings who are Receiving Care in Youth-Friendly Clinics.

OBJECTIVE: Adolescents with HIV (AWH) have higher rates of detectable viral loads (DVL) than adults. We sought to identify clinical and psychosocial p...

Machine learning-driven conditional survival prediction model for atypical teratoid/rhabdoid tumor.

PURPOSE: Atypical teratoid/rhabdoid tumor (AT/RT) is a rare and highly malignant pediatric brain tumor with dismal prognosis. We aimed to characterize...

Prediction of hospitalisation in young children with pneumonia in Malawi: A machine learning-based approach.

BACKGROUND: Globally, pneumonia remains the single biggest cause of mortality in children under 5 years of age. This study sought to train and test a ...