AIMC Topic: Child, Preschool

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A comprehensive study based on machine learning models for early identification Mycoplasma pneumoniae infection in segmental/lobar pneumonia.

Scientific reports
Segmental/lobar pneumonia in children following Mycoplasma pneumoniae (MP) infection has a significant threat to the children's health, so early recognition of MP infection is critical to reduce the severity and improve the prognosis of segmental/lob...

GenAI exceeds clinical experts in predicting acute kidney injury following paediatric cardiopulmonary bypass.

Scientific reports
The emergence of large language models (LLMs) opens new horizons to leverage, often unused, information in clinical text. Our study aims to capitalise on this new potential. Specifically, we examine the utility of text embeddings generated by LLMs in...

Personalized azithromycin treatment rules for children with watery diarrhea using machine learning.

Nature communications
We use machine learning to identify innovative strategies to target azithromycin to the children with watery diarrhea who are most likely to benefit. Using data from a randomized trial of azithromycin for watery diarrhea (NCT03130114), we develop per...

Fully automated measurement of paediatric cerebral palsy pelvic radiographs with BoneFinder : external validation using a national surveillance database.

The bone & joint journal
AIMS: BoneFinder is a machine-learning tool that can automatically calculate Reimers migration percentage (RMP) and head-shaft angle (HSA) from paediatric cerebral palsy (CP) pelvic radiographs. This study's primary aim was to compare BoneFinder's fu...

Artificial Intelligence Iterative Reconstruction for Dose Reduction in Pediatric Chest CT: A Clinical Assessment via Below 3 Years Patients With Congenital Heart Disease.

Journal of thoracic imaging
PURPOSE: To assess the performance of a newly introduced deep learning-based reconstruction algorithm, namely the artificial intelligence iterative reconstruction (AIIR), in reducing the dose of pediatric chest CT by using the image data of below 3-y...

Developing a novel medulloblastoma diagnostic with miRNA biomarkers and machine learning.

Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
BACKGROUND: Medulloblastoma (MB) is the most common malignant brain tumor in children. Current diagnostic methods, such as MRI and lumbar puncture, are invasive and not sensitive enough, making early diagnosis challenging. MicroRNAs (miRNAs) have eme...

A novel speech signal feature extraction technique to detect speech impairment in children accurately.

Computers in biology and medicine
Speech signal processing and extracting useful information from speech signal is necessary for speech language impairment (SLI) detection in children. Although different features has been suggested for SLI detection, there is still a scope exist for ...

AI-supported versus manual microscopy of Kato-Katz smears for diagnosis of soil-transmitted helminth infections in a primary healthcare setting.

Scientific reports
Soil-transmitted helminths primarily comprise Ascaris lumbricoides, Trichuris trichiura, and hookworms, infecting more than 600 million people globally, particularly in underserved communities. Manual microscopy of Kato-Katz thick smears is a widely ...

Breath profiles in paediatric allergic asthma by proton transfer reaction mass spectrometry.

BMJ open respiratory research
INTRODUCTION: Enhancing paediatric asthma diagnosis is crucial. Molecular analysis of exhaled breath is a rapidly evolving field aimed at harnessing established and innovative technologies for clinical applications. This study evaluates the feasibili...