AIMC Topic: Child

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Artificial Intelligence and Teleradiology in Pediatric Radiology: A Survey by the Society for German-speaking Pediatric Radiologists (GPR) and the Swiss Society for Pediatric Radiology (SGPR).

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
The aim of our study was to assess the attitudes towards AI and teleradiology and their current usage in pediatric radiology within German-speaking countries.From March to May 2023, we conducted an anonymous online survey among members of the Society...

Diagnosis of Sacroiliitis Through Semi-Supervised Segmentation and Radiomics Feature Analysis of MRI Images.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Sacroiliitis is a hallmark of ankylosing spondylitis (AS), and early detection plays an important role in managing the condition effectively. MRI is commonly used for diagnosing sacroiliitis, traditional methods often depend on subjective...

Machine learning reveals sex differences in distinguishing between conduct-disordered and neurotypical youth based on emotion processing dysfunction.

BMC psychiatry
BACKGROUND: Theoretical models of conduct disorder (CD) highlight that deficits in emotion recognition, learning, and regulation play a pivotal role in CD etiology. With CD being more prevalent in boys than girls, various theories aim to explain this...

Machine Learning-Based Pediatric Early Warning Score: Patient Outcomes in a Pre- Versus Post-Implementation Study, 2019-2023.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies
OBJECTIVES: To describe the deployment of pediatric Calculated Assessment of Risk and Triage (pCART), a machine learning (ML) model to predict the risk of the direct ward to the ICU transfer within 12 hours, and the associated improved outcomes among...

A living scoping review and online repository of artificial intelligence models in pediatric urology: Results from the AI-PEDURO collaborative.

Journal of pediatric urology
INTRODUCTION: Artificial intelligence (AI) is increasingly being applied across pediatric urology. We provide a living scoping review and online repository developed by the AI in PEDiatric UROlogy (AI-PEDURO) collaborative that summarizes the current...

Deep learning radiomics nomogram for preoperatively identifying moderate-to-severe chronic cholangitis in children with pancreaticobiliary maljunction: a multicenter study.

BMC medical imaging
BACKGROUND: Long-term severe cholangitis can lead to dense adhesions and increased fragility of the bile duct, complicating surgical procedures and elevating operative risk in children with pancreaticobiliary maljunction (PBM). Consequently, preopera...

Artificial Intelligence in Pediatric Endocrinology.

Advances in pediatrics
The rapid technological progress over the last couple of decades has paved the way for innovative methods capable of solving scientific questions at a rate far exceeding human capabilities. One prime example is the field of artificial intelligence (A...

Machine learning for predicting severe dengue in Puerto Rico.

Infectious diseases of poverty
BACKGROUND: Distinguishing between non-severe and severe dengue is crucial for timely intervention and reducing morbidity and mortality. World Health Organization (WHO)-recommended warning signs offer a practical approach for clinicians but have limi...

An Explainable Unified Framework of Spatio-Temporal Coupling Learning With Application to Dynamic Brain Functional Connectivity Analysis.

IEEE transactions on medical imaging
Time-series data such as fMRI and MEG carry a wealth of inherent spatio-temporal coupling relationship, and their modeling via deep learning is essential for uncovering biological mechanisms. However, current machine learning models for mining spatio...

[Artificial intelligence in paediatric pneumology - opportunities and unanswered questions].

Klinische Padiatrie
Artificial intelligence (AI) is already being used in most medical disciplines, including paediatric pneumology. This review describes current developments in AI-supported technologies and discusses their potential for the diagnosis and treatment of ...