AI Medical Compendium Topic:
Child

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Enhancing pediatric pneumonia diagnosis through masked autoencoders.

Scientific reports
Pneumonia, an inflammatory lung condition primarily triggered by bacteria, viruses, or fungi, presents distinctive challenges in pediatric cases due to the unique characteristics of the respiratory system and the potential for rapid deterioration. Ti...

A survey of patient acceptability of the use of artificial intelligence in the diagnosis of paediatric fractures: an observational study.

Annals of the Royal College of Surgeons of England
INTRODUCTION: This study aimed to assess carer attitudes towards the use of artificial intelligence (AI) in management of fractures in paediatric patients. As fracture clinic services come under increasing pressure, innovative solutions are needed to...

Pediatric endoscopy: how can we improve patient outcomes and ensure best practices?

Expert review of gastroenterology & hepatology
INTRODUCTION: Strategies to promote high-quality endoscopy in children require consensus around pediatric-specific quality standards and indicators. Using a rigorous guideline development process, the international Pediatric Endoscopy Quality Improve...

Radiographic morphology of canines tested for sexual dimorphism via convolutional-neural-network-based artificial intelligence.

Morphologie : bulletin de l'Association des anatomistes
The permanent left mandibular canines have been used for sexual dimorphism when human identification is necessary. Controversy remains whether the morphology of these teeth is actually useful to distinguish males and females. This study aimed to asse...

Identification of autism spectrum disorder using multiple functional connectivity-based graph convolutional network.

Medical & biological engineering & computing
Presently, the combination of graph convolutional networks (GCN) with resting-state functional magnetic resonance imaging (rs-fMRI) data is a promising approach for early diagnosis of autism spectrum disorder (ASD). However, the prevalent approach in...

Machine learning-assisted prediction of trabeculectomy outcomes among patients of juvenile glaucoma by using 5-year follow-up data.

Indian journal of ophthalmology
OBJECTIVE: To develop machine learning (ML) models, using pre and intraoperative surgical parameters, for predicting trabeculectomy outcomes in the eyes of patients with juvenile-onset primary open-angle glaucoma (JOAG) undergoing primary surgery.

Real-world artificial intelligence-based interpretation of fundus imaging as part of an eyewear prescription renewal protocol.

Journal francais d'ophtalmologie
OBJECTIVE: A real-world evaluation of the diagnostic accuracy of the OpthaiĀ® software for artificial intelligence-based detection of fundus image abnormalities in the context of the French eyewear prescription renewal protocol (RNO).

Artificial intelligence in paediatrics: Current events and challenges.

Anales de pediatria
This article examines the use of artificial intelligence (AI) in the field of paediatric care within the framework of the 7P medicine model (Predictive, Preventive, Personalized, Precise, Participatory, Peripheral and Polyprofessional). It highlights...

An artificial intelligence language model improves readability of burns first aid information.

Burns : journal of the International Society for Burn Injuries
AIMS: This study aimed to assess the potential of using an artificial intelligence (AI) large language model to improve the readability of burns first aid information.