Pediatrics

Latest AI and machine learning research in pediatrics for healthcare professionals.

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Comparative Evaluation of Advanced AI Reasoning Models in Pediatric Clinical Decision Support: ChatGPT O1 vs. DeepSeek-R1

The adoption of advanced reasoning models, such as ChatGPT O1 and DeepSeek-R1, represents a pivotal step forward in clinical decision support, particularly in pediatrics. ChatGPT O1 employs “chain-of-thought reasoning” (CoT) to enhance structured problem-solving, while DeepSeek-R1 introduces self-reflection capabilities through reinforcement learning. This study aimed to evaluate the diagnostic ac...

SYSTEMS AND NETWORK BIOLOGY ANALYSIS COMBINED WITH MACHINE LEARNING IDENTIFIES KEY IMMUNE RESPONSE PROFILES AND POTENTIAL CORRELATES OF PROTECTION FOR THE M72/AS01E TUBERCULOSIS VACCINE

Tuberculosis claims around 1.5 million lives annually. The M72/AS01E vaccine candidate is an innovative effort demonstrating a 50% reduction in the incidence of active TB in adults. However, optimization and effective immunization strategies against TB depends heavily on precise identification of specific molecular signatures active in vaccine protection. In this study, we employed weighted gene c...

Neuroprognostication via Spatially-Informed Machine Learning Following Hypoxic-Ischemic Injury

Can machine learning be used to reliably and accurately predict 18-month developmental outcomes from neonatal brain MRI following perinatal hypoxic-is...

Assessing Large Language Model Performance Related to Aging in Genetic Conditions

Unlike some health conditions that have been extensively delineated throughout the lifespan, many genetic conditions are largely described in pediatri...

Retinal vascularization rate predicts retinopathy of prematurity and remains unaffected by low-dose bevacizumab treatment

To assess the rate of retinal vascularisation derived from ultra-widefield (UWF) imaging-based retinopathy of prematurity (ROP) screening as predictor...

From Patient Voices to Policy: Data Analytics Reveals Patterns in Ontario’s Hospital Feedback

Patient satisfaction is a central measure of high-performing healthcare systems, yet real-world evaluations at scale remain challenging. In this study...

Introducing and Evaluating the Patient Report Template for AI-Powered Nursing Handoffs

This study evaluates the effectiveness of the Patient Report Template (PRT) in addressing inefficiencies in nursing workflows related to electronic he...

The lived experience of social anxiety disorder: A conceptual model based on published literature and social media listening

Social anxiety disorder (SAD) affects up to 1 in 8 individuals over their lifetime and is characterized by an intense fear of social situations where ...

A deep learning model for clinical outcome prediction using longitudinal inpatient electronic health records

Recent advances in deep learning show significant potential in analyzing continuous monitoring electronic health records (EHR) data for clinical outco...

Using large language models to understand the public discourse towards vaccination in Brazil between January 2013 and December 2019

Vaccination against infectious diseases prevents diseases, saves lives, and reduces healthcare costs. However, trust, accessibility, and public percep...

PH-LLM: Public Health Large Language Models for Infoveillance

The effectiveness of public health intervention, such as vaccination and social distancing, relies on public support and adherence. Social media has e...

Phenotyping Adolescent Endometriosis: Characterizing Symptom Heterogeneity Through Note- and Patient-Level Clustering

Pelvic pain (dysmenorrhea and non-menstrual) is the most common presentation of adolescent endometriosis, but symptoms vary between and within patient...

Machine Learning Models for Dynamic Assessment of Extubation Readiness in Pediatric Critical Care

Determining the optimal timing for extubation in critically ill children remains challenging, with premature extubation leading to increased morbidity...

The Impact of Negative Emotions on Adolescents’ Nonsuicidal Self-Injury Thoughts: An Integrated Application of Machine Learning and Multilevel Logistic Models

Non-Suicidal Self-Injury (NSSI) is a prevalent and complex behavior among adolescents, often linked to negative emotions such as loneliness, anxiety, ...

Classification of Pediatric Dental Diseases from Panoramic Radiographs using Natural Language Transformer and Deep Learning Models

Accurate classification of pediatric dental diseases from panoramic radiographs is crucial for early diagnosis and treatment planning. This study expl...

The role of artificial intelligence in the application of the integrated electronic health records and patient-generated health data

This scoping review aims to identify and understand the role of artificial intelligence in the application of integrated electronic health records (EH...

Sentiment analysis of employees and COVID-19 vaccine hesitancy at workplace

Vaccination is a potent means to combat the spread of infectious disease epidemics or pandemics, such as the COVID-19 pandemic. However, getting suffi...

Data-Driven Early Prediction of Cerebral Palsy Using AutoML and interpretable kinematic features

Early identification of cerebral palsy (CP) remains a major challenge due to the reliance on expert assessments that are time-intensive and not scalab...

Segmentation-Free Pretherapeutic Assessment of BRAF-Status in Pediatric Low-Grade Gliomas

BRAF status is crucial for treating pediatric low-grade gliomas (pLGG) and can be assessed non-invasively from segmented tumor regions on MRI using ma...

Predicting Levels of Anemia among Adolescents in Ethiopia Using homogeneous ensemble Machine Learning algorithm

Anemia significantly impacts adolescent girls’ health and quality of life in Ethiopia. Effective interventions require identifying key risk factors an...

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