AIMC Topic: Infant, Newborn

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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...

Collaborative targeted learning using regression shrinkage.

Statistics in medicine
Causal inference practitioners are routinely presented with the challenge of model selection and, in particular, reducing the size of the covariate set with the goal of improving estimation efficiency. Collaborative targeted minimum loss-based estima...

Learning-based deformable registration for infant MRI by integrating random forest with auto-context model.

Medical physics
PURPOSE: Accurately analyzing the rapid structural evolution of human brain in the first year of life is a key step in early brain development studies, which requires accurate deformable image registration. However, due to (a) dynamic appearance and ...

The ResQu Index: A new instrument to appraise the quality of research on birth place.

PloS one
OBJECTIVE: Place of birth is a known determinant of health care outcomes, interventions and costs. Many studies have examined the maternal and perinatal outcomes when women plan to give birth in hospitals compared with births in birth centres or at h...

Learning and combining image neighborhoods using random forests for neonatal brain disease classification.

Medical image analysis
It is challenging to characterize and classify normal and abnormal brain development during early childhood. To reduce the complexity of heterogeneous data population, manifold learning techniques are increasingly applied, which find a low-dimensiona...

Predicting all-cause risk of 30-day hospital readmission using artificial neural networks.

PloS one
Avoidable hospital readmissions not only contribute to the high costs of healthcare in the US, but also have an impact on the quality of care for patients. Large scale adoption of Electronic Health Records (EHR) has created the opportunity to proacti...

Bone Fusion in Normal and Pathological Development is Constrained by the Network Architecture of the Human Skull.

Scientific reports
Craniosynostosis, the premature fusion of cranial bones, affects the correct development of the skull producing morphological malformations in newborns. To assess the susceptibility of each craniofacial articulation to close prematurely, we used a ne...