Urinary obstruction causes injury to the renal medulla, impairing the ability to concentrate urine, and increasing the risk of progressive kidney disease. However, the regenerative capacity of the renal medulla after reversal of obstruction is poorly understood. To investigate this, we developed a mouse model of reversible urinary obstruction.
View Article and Find Full Text PDFThis study aims to develop a Machine Learning model to assess the risks faced by COVID-19 patients in a hospital setting, focusing specifically on predicting the complications leading to Intensive Care Unit (ICU) admission or mortality, which are minority classes compared to the majority class of discharged patients. We operate within a multiclass framework comprising three distinct classes, and address the challenge of dataset imbalance, a common source of model bias. To effectively manage this, we introduce the Multi-Thresholding meta-algorithm (MTh), an innovative output-level methodology that extends traditional thresholding from binary to multiclass classification.
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