AIMC Topic: Child

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Different spexin level in obese vs normal weight children and its relationship with obesity related risk factors.

Nutrition, metabolism, and cardiovascular diseases : NMCD
BACKGROUND AND AIMS: Spexin (SPX) is a novel peptide recently discovered as an important regulatory adipokine in obesity and related metabolic diseases. The aim of the current study was to determine the potential role of Circulating levels of SPX in ...

Analyzing gene expression data for pediatric and adult cancer diagnosis using logic learning machine and standard supervised methods.

BMC bioinformatics
BACKGROUND: Logic Learning Machine (LLM) is an innovative method of supervised analysis capable of constructing models based on simple and intelligible rules. In this investigation the performance of LLM in classifying patients with cancer was evalua...

Comparison of morphometric parameters in prediction of hydrocephalus using random forests.

Computers in biology and medicine
Ventricles of the human brain enlarge with aging, neurodegenerative diseases, intrinsic, and extrinsic pathologies. The morphometric examination of neuroimages is an effective approach to assess structural changes occurring due to diseases such as hy...

Prediction of visual outcomes by an artificial neural network following intravitreal injection and laser therapy for retinopathy of prematurity.

The British journal of ophthalmology
AIMS: To construct a program to predict the visual acuity (VA), best corrected VA (BCVA) and spherical equivalent (SE) of patients with retinopathy of prematurity (ROP) from 3 to 12 years old after intravitreal injection (IVI) of anti-vascular endoth...

Use of deep learning to detect personalized spatial-frequency abnormalities in EEGs of children with ADHD.

Journal of neural engineering
OBJECTIVE: Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent neurobehavioral disorders. Studies have tried to find the neural correlations of ADHD with electroencephalography (EEG). Due to the heterogeneity in the ADHD popu...

Development of artificial neural network model for prediction of post-streptococcus mutans in dental caries.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Streptococcus mutans is the primary initiator and most common organism associated with dental caries. Prediction of post-Streptococcus mutans favours in the selection of appropriate caries excavation method which eventually ...

Developing Children's Oral Health Assessment Toolkits Using Machine Learning Algorithm.

JDR clinical and translational research
OBJECTIVES: Evaluating children's oral health status and treatment needs is challenging. We aim to build oral health assessment toolkits to predict Children's Oral Health Status Index (COHSI) score and referral for treatment needs (RFTN) of oral heal...

A new deep learning-based method for the detection of gait events in children with gait disorders: Proof-of-concept and concurrent validity.

Journal of biomechanics
The stance and swing phases of the gait cycle are defined by foot strike (FS) and foot off (FO). Accurate determination of these events is thus an essential component of 3D motion recordings processing. Several methods have been developed for the aut...

The feasibility of developing biomarkers from peripheral blood mononuclear cell RNAseq data in children with juvenile idiopathic arthritis using machine learning approaches.

Arthritis research & therapy
BACKGROUND: The response to treatment for juvenile idiopathic arthritis (JIA) can be staged using clinical features. However, objective laboratory biomarkers of remission are still lacking. In this study, we used machine learning to predict JIA activ...