AIMC Topic: Child

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Prediction of Poor Visual Outcomes at Idiopathic Intracranial Hypertension Diagnosis Using a Supervised Machine Learning Algorithm.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society
BACKGROUND: Idiopathic intracranial hypertension (IIH) is a vision-threatening disorder mainly affecting women of a reproductive age. Prompt diagnosis and intervention are vital to prevent vision loss, but validated tools to predict visual outcomes a...

Ecological Network Analysis: Utilizing Machine Learning to Unravel the Effects of Multilevel Pathways of Moderate⁃to⁃Vigorous Physical Activity Facilitators Among School Children.

Research quarterly for exercise and sport
The objective of the present study was to ascertain whether the association between moderate-to-vigorous intensity physical activity (MVPA) levels and individual, interpersonal, organizational, and environmental factors among school children is influ...

Using explainable machine learning to investigate the relationship between childhood maltreatment, positive psychological traits, and CPTSD symptoms.

European journal of psychotraumatology
The functional impairment resulting from CPTSD symptoms is enduring and far-reaching. Existing research has found that CPTSD symptoms are closely associated with childhood maltreatment; however, researchers debate whether CPTSD symptoms are predomin...

Construction and validation of a predictive model for meningoencephalitis in pediatric scrub typhus based on machine learning algorithms.

Emerging microbes & infections
To retrospectively analyze the clinical characteristics of pediatric scrub typhus (ST) with meningoencephalitis (STME) and to construct and validate predictive models using machine learning.Clinical data were collected from 100 cases of pediatric STM...

Identification and validation of susceptibility modules and hub genes in polyarticular juvenile idiopathic arthritis using WGCNA and machine learning.

Autoimmunity
BACKGROUND: Juvenile idiopathic arthritis (JIA), superseding juvenile rheumatoid arthritis (JRA), is a chronic autoimmune disease affecting children and characterized by various types of childhood arthritis. JIA manifests clinically with joint inflam...

Machine learning identifies prominent risk factors for depressive symptoms among Chinese children and adolescents.

Journal of affective disorders
BACKGROUND: Identifying key risk factors for depressive symptoms in children and adolescents is crucial for prevention. However, few studies have explored this topic. This study aimed to examine the prevalence of depressive symptoms in Chinese childr...

[Opportunities and challenges in the pathological diagnosis of pediatric tumors in the molecular and artificial intelligence era].

Zhonghua bing li xue za zhi = Chinese journal of pathology
Pediatric tumors differ significantly from adult cancers, possessing unique developmental origins, histological features, and molecular genetic changes. With the rapid advancement of multi-omics technologies, such as genomics, transcriptomics, proteo...

Utilization of a Digital Automated Cell Morphology Analyzer Results for Determining Differential White Blood Cell Counts in a Turkish Pediatric Population.

The journal of applied laboratory medicine
BACKGROUND: Manual morphological analysis of peripheral blood smears (PBS) with light microscopy is an essential diagnostic and monitoring tool. Recently, automated morphology analyzers have been developed that can preclassify cells using artificial ...

Machine learning using serial changes in proteinuria during initial steroid therapy to predict treatment response and immunosuppressant use in pediatric idiopathic nephrotic syndrome.

Clinical and experimental nephrology
BACKGROUND: Epidemiological studies on idiopathic nephrotic syndrome (INS) in children have identified no definitive factors predicting steroid-resistant nephrotic syndrome (SRNS) or frequent relapsing nephrotic syndrome. Research using machine learn...

Evaluation of an AI facial recognition system for Turner Syndrome screening and facial complexity: a prospective cohort.

International journal of medical informatics
PURPOSE: Artificial intelligence-based facial recognition (AI-FR) is promising in diagnosis of diseases with distinct facial features. Our team has retrospectively constructed an AI-FR system for Turner Syndrome (TS) based on 1295 facial photographs ...