Pediatrics

The adaptive large language models for vaccine prediction: A novel approach to vaccine demand prediction with engineered deviation prompts.

Accurate vaccine demand forecasting is crucial for minimizing wastage and ensuring efficient immunization programs. In this study, we introduce an Adaptive Large Language Model for Vaccine Prediction (ALLMVP) that integrates large language model (LLM) architectures with an adaptive value correction mechanism. Using vaccination record data from Xuhui District, Shanghai, China (2014-2022), we conduc...

A cautionary tale for AI and machine learning in psychiatry.

Artificial intelligence (AI) and machine learning (ML) have seen remarkable growth in mental health applications over the past few decades, demonstrating significant potential to transform psychiatric care. Despite these advancements, the translation of AI systems into clinical practice remains fraught with challenges. This Perspective examines critical hurdles in psychiatric AI research, emphasiz...

Promoting clinical trials in pediatric IgA nephropathy through extrapolation: an artificial intelligence-enhanced literature review of the disease in pediatrics sponsored by the Kidney Health Initiative.

BACKGROUND: There is an urgent need to evaluate the efficacy of novel therapeutics that have been approved for use in adults with IgA nephropathy (IgA...

Artificial intelligence and robotics in global neurosurgery: A scoping review.

OBJECTIVE: Artificial intelligence (AI) and robotics are transforming neurosurgical care; however, the application of these technologies in low- and m...

Integrating the Glycemia Risk Index Into Clinical Practice and Research: A Consensus Report.

A panel of experts in the use of continuous glucose monitoring (CGM) data in the treatment of diabetes met in Burlingame, California on October 27, 20...

Predicting rapid weight gain in six-month-old infants: an exploratory modeling study.

BACKGROUND: Rapid weight gain (RWG) in early life is a significant risk factor for childhood obesity. Its multifactorial etiology warrants exploratory...

Artificial intelligence innovations in substance use prevention on social media: A scoping review.

OBJECTIVES: This scoping review examined the current application of artificial intelligence (AI)/machine learning (ML) models on social media platform...

Evaluating Artificial Intelligence-Generated Nursing Care Plans: A Scenario-Based Comparative Study of Accuracy, Completeness, Quality, and Readability.

AIM: This study aimed to evaluate the ability of three generative artificial intelligence tools (ChatGPT, Gemini and DeepSeek) to generate clinically ...

Machine learning framework for early detection of polio outbreaks from acute flaccid paralysis surveillance data.

Poliomyelitis remains a global public health concern despite remarkable progress toward eradication. The continued circulation of vaccine-derived poli...

Differential quadruple pattern: A new EEG signal classification framework.

EEG signals are the letters of the brain and reflect neural activity. Abnormal EEG patterns indicate brain disorders such as epilepsy. Recently, machi...

Cross-Cultural Differences in Public Discourse on COVID-19 Vaccination in the United States and South Korea: Cross-Sectional Analysis Using Natural Language Processing.

BACKGROUND: The COVID-19 vaccine was introduced as a crucial tool to combat the pandemic. However, concerns about its effectiveness, side effects, and...

Classification of suicide attempt history in adolescents with affective disorders: An exploratory machine learning study.

INTRODUCTION: Diagnosis of affective disorders among adolescent population links with the high risk of suicide attempt. The use of clinical psychologi...

Clinical application progress and prospects of non-invasive preimplantation genetic testing (niPGT): A review.

Preimplantation genetic testing (PGT) is a critical tool in reproductive medicine for selecting genetically healthy embryos, thereby reducing the risk...

A data-centric approach to detecting and mitigating demographic bias in pediatric mental health text.

BACKGROUND: Healthcare Artificial Intelligence (AI) offers transformative potential but often inherits biases from training data, worsening disparitie...

Use of artificial intelligence for outcome assessment in pediatric rehabilitation: a scoping review.

In Situ-Grown Zeolitic Imidazolate Framework-8@Mg-Fe Layered Double-Hydroxide Heterostructure with Enhanced Adsorption Properties: Insights from Experimental and Computational Investigations.

The removal of organic pollutants, especially dyes, from wastewater remains a critical environmental challenge. Metal-organic frameworks (MOF) and lay...

Speech-to-Speech Voice-Cloning Care (SVCC) for improving ICU-acquired anxiety for critically ill patients in a tertiary hospital in Beijing, China: protocol of a randomised, controlled trial.

INTRODUCTION: Intensive care unit (ICU) visiting restrictions in hospitals, implemented due to infection control and other factors, limited contact be...

Accuracy, quality, and readability analyses of responses from large language models to questions on pediatric dental sedation.

Generative Artificial Intelligence: Implications for Families and Pediatricians.

Generative artificial intelligence (AI) technologies, capable of producing original text, images, audio, and video, are increasingly embedded in child...

Determinants of labor epidural analgesia uptake and associations with maternal-neonatal outcomes: a stratified cohort study with risk prediction modeling.

BACKGROUND: Labor pain is a major physiological and psychological stressor for women during childbirth. Epidural analgesia is widely recognized as the...