Synthetic data have emerged as an attractive option for developing machine-learning methods in human neuroimaging, particularly in magnetic resonance imaging (MRI)-a modality where image contrast depends enormously on acquisition hardware and parameters. This retrospective paper reviews a family of recently proposed methods, based on synthetic data, for generalizable machine learning in brain MRI analysis. Central to this framework is the concept of domain randomization, which involves training neural networks on a vastly diverse array of synthetically generated images with random contrast properties.
View Article and Find Full Text PDFImportance: Congenital Zika syndrome (CZS) can lead to a range of developmental and neurological issues, which increases the risk of early death. However, the all-cause and cause-specific mortality in children with CZS in the first 5 years of life remain unknown.
Objective: To compare the hazard of all-cause and cause-specific mortality before age 5 years among children with and without CZS in Brazil.
ACS Environ Au
January 2025
This study reviews the literature on mercury (Hg) pollution in the Tapajós River basin from 1992 to 2022, focusing on the bioaccumulation in fish and the associated health risks to humans via ingesting contaminated species. Variability in Hg bioaccumulation was analyzed from both spatial (sub-basins) and ecological (trophic levels) perspectives. Mercury concentrations in fish muscle tissue and spatial differences in Hg levels were analyzed using nonparametric Kruskal-Wallis ANOVA and mapped with Inverse Distance Weighting.
View Article and Find Full Text PDFBackground Congenital Zika Syndrome (CZS) has been linked to a wide spectrum of abnormalities. However, differences in hospitalization patterns between children with and without CZS have not yet been investigated. Methods We compared rates of hospital admissions for all and specific diseases, proportions of admission causes, and total length of hospital stay (LOS) between children with CZS and those without the syndrome.
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