AIMC Topic: Child

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Achieving SDoH Resource Equity in PICU Using an AI-Enabled Patient Navigator.

Studies in health technology and informatics
Trauma care coordination in the pediatric intensive care unit (PICU), including personalization of resources based on social determinants of health (SDoH), is challenging for already strained healthcare providers. Patient SDoH data collection is inco...

Extracting Pediatric Information from Summaries of Product Characterics with a Large Language Model and No-Code.

Studies in health technology and informatics
Accurate medication information is important for children, as dosing errors can have severe consequences compared to adults. We propose an automated method to extract pediatric information from Summaries of Product Characteristics (SPC). We used AirO...

Characterizing ASD Subtypes Using Morphological Features from sMRI with Unsupervised Learning.

Studies in health technology and informatics
In this study, we attempted to identify the subtypes of autism spectrum disorder (ASD) with the help of anatomical alterations found in structural magnetic resonance imaging (sMRI) data of the ASD brain and machine learning tools. Initially, the sMRI...

ArtInsight: A Multimodal AI Framework for Interpreting Children's Drawings and Enhancing Emotional Understanding.

Studies in health technology and informatics
Recent advancements in multimodal image-to-text models have greatly enhanced the interpretation of children's drawings for emotional understanding purposes. This paper introduces a framework that analyzes these drawings to fully automatically generat...

Predicting sepsis treatment decisions in the paediatric emergency department using machine learning: the AiSEPTRON study.

BMJ paediatrics open
BACKGROUND: Early identification of children at risk of sepsis in emergency departments (EDs) is crucial for timely treatment and improved outcomes. Existing risk scores and criteria for paediatric sepsis are not well-suited for early diagnosis in ED...

Single-cell RNA sequencing reveals immunological link between house dust mite allergy and childhood asthma.

Scientific reports
Allergic asthma in children is typically associated with house dust mites (HDM) as the key allergen. Nevertheless, the diagnostic rate remains below 60% due to the absence of specific symptoms and diagnostic markers, which hinders the implementation ...

Effectiveness of AI-Driven Conversational Agents in Improving Mental Health Among Young People: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: The increasing prevalence of mental health issues among adolescents and young adults, coupled with barriers to accessing traditional therapy, has led to growing interest in artificial intelligence (AI)-driven conversational agents (CAs) a...

Transforming 3D MRI to 2D Feature Maps Using Pre-Trained Models for Diagnosis of Attention Deficit Hyperactivity Disorder.

Tomography (Ann Arbor, Mich.)
According to the World Health Organization (WHO), approximately 5% of children and 2.5% of adults suffer from attention deficit hyperactivity disorder (ADHD). This disorder can have significant negative consequences on people's lives, particularly c...

Development and validation of an early diagnosis model for severe mycoplasma pneumonia in children based on interpretable machine learning.

Respiratory research
BACKGROUND: Pneumonia is a major threat to the health of children, especially those under the age of five. Mycoplasma  pneumoniae infection is a core cause of pediatric pneumonia, and the incidence of severe mycoplasma pneumoniae pneumonia (SMPP) has...