AIMC Topic: Child, Preschool

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A novel method for predicting kidney stone type using ensemble learning.

Artificial intelligence in medicine
The high morbidity rate associated with kidney stone disease, which is a silent killer, is one of the main concerns in healthcare systems all over the world. Advanced data mining techniques such as classification can help in the early prediction of t...

Vitamin D Deficiency and Atopic Dermatitis: Consider Disease, Race, and Body Mass.

Skinmed
Vitamin D deficiency causes rickets, but has been associated with various diseases, including atopic dermatitis (AD). This study analyzes serum vitamin D in pediatric medical center patients with AD and potential confounding factors. At Cardinal Glen...

Developing a Machine Learning System for Identification of Severe Hand, Foot, and Mouth Disease from Electronic Medical Record Data.

Scientific reports
Children of severe hand, foot, and mouth disease (HFMD) often present with same clinical features as those of mild HFMD during the early stage, yet later deteriorate rapidly with a fulminant disease course. Our goal was to: (1) develop a machine lear...

Classification of hospital admissions into emergency and elective care: a machine learning approach.

Health care management science
Rising admissions from emergency departments (EDs) to hospitals are a primary concern for many healthcare systems. The issue of how to differentiate urgent admissions from non-urgent or even elective admissions is crucial. We aim to develop a model f...

Vitamin C evaluation in foods for infants and young children by a rapid and accurate analytical method.

Food chemistry
The validation of a rapid, precise (RSD < 4.6%), reliable and sensitive (LOD = 0.026 µg/mL) liquid chromatography method for vitamin C quantification in foods (infant formulae, n = 4; follow-on formulae, n = 3; processed cereal based-foods, n = 7; an...

FUZZY COMPUTATIONAL MODELS TO EVALUATE THE EFFECTS OF AIR POLLUTION ON CHILDREN.

Revista paulista de pediatria : orgao oficial da Sociedade de Pediatria de Sao Paulo
OBJECTIVE: To build a fuzzy computational model to estimate the number of hospitalizations of children aged up to 10 years due to respiratory conditions based on pollutants and climatic factors in the city of São José do Rio Preto, Brazil.

Performance of a Deep-Learning Neural Network Model in Assessing Skeletal Maturity on Pediatric Hand Radiographs.

Radiology
Purpose To compare the performance of a deep-learning bone age assessment model based on hand radiographs with that of expert radiologists and that of existing automated models. Materials and Methods The institutional review board approved the study....