AIMC Topic: Child

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Significant predictors of mathematical literacy for top-tiered countries/economies, Canada, and the United States on PISA 2012: Case for the sparse regression model.

The British journal of educational psychology
BACKGROUND: National ranking from the triennial Programme of International Student Assessment (PISA) often serves as a barometer of national performance and human capital. Though excessive student- and school-level covariates (n > 700) may prove intr...

Urinary concentrations and profiles of organophosphate and pyrethroid pesticide metabolites and phenoxyacid herbicides in populations in eight countries.

Environment international
Concentrations of nine metabolites of organophosphate and pyrethroid insecticides, as well as two phenoxy herbicides, were determined in 322 urine samples collected from eight countries during 2006-2014 by high-performance liquid chromatography-tande...

Analysis of tuberculosis disease through Raman spectroscopy and machine learning.

Photodiagnosis and photodynamic therapy
We present the effectiveness of Raman spectroscopy (RS) in combination with machine learning for screening and analysis of blood sera collected from tuberculosis patients. Blood samples of 60 patients have confirmed active pulmonary tuberculosis and ...

Regression Convolutional Neural Network for Automated Pediatric Bone Age Assessment From Hand Radiograph.

IEEE journal of biomedical and health informatics
Skeletal bone age assessment is a common clinical practice to investigate endocrinology, and genetic and growth disorders of children. However, clinical interpretation and bone age analyses are time-consuming, labor intensive, and often subject to in...

The PInSoRo dataset: Supporting the data-driven study of child-child and child-robot social dynamics.

PloS one
The study of the fine-grained social dynamics between children is a methodological challenge, yet a good understanding of how social interaction between children unfolds is important not only to Developmental and Social Psychology, but recently has b...

Deep Geodesic Learning for Segmentation and Anatomical Landmarking.

IEEE transactions on medical imaging
In this paper, we propose a novel deep learning framework for anatomy segmentation and automatic landmarking. Specifically, we focus on the challenging problem of mandible segmentation from cone-beam computed tomography (CBCT) scans and identificatio...

Radiomics features on non-contrast-enhanced CT scan can precisely classify AVM-related hematomas from other spontaneous intraparenchymal hematoma types.

European radiology
OBJECTIVE: To investigate the classification ability of quantitative radiomics features extracted on non-contrast-enhanced CT (NECT) image for discrimination of AVM-related hematomas from those caused by other etiologies.

Detection of Traumatic Pediatric Elbow Joint Effusion Using a Deep Convolutional Neural Network.

AJR. American journal of roentgenology
OBJECTIVE: The purpose of this study is to determine whether a deep convolutional neural network (DCNN) trained on a dataset of limited size can accurately diagnose traumatic pediatric elbow effusion on lateral radiographs.

Potential identification of vitamin B6 responsiveness in autism spectrum disorder utilizing phenotype variables and machine learning methods.

Scientific reports
We investigated whether machine learning methods could potentially identify a subgroup of persons with autism spectrum disorder (ASD) who show vitamin B6 responsiveness by selected phenotype variables. We analyzed the existing data from our intervent...

Diagnosis of urinary tract infection based on artificial intelligence methods.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Urinary tract infection (UTI) is a common disease affecting the vast majority of people. UTI involves a simple infection caused by urinary tract inflammation as well as a complicated infection that may be caused by an inflam...