Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Objective This study focused on the preferences for psychological assistance and associated factors among Chinese healthcare workers (HCWs) during the COVID-19 pandemic. Design Cross-sectional ...
Background Previous studies have suggested an adverse role of epicardial adipose tissue (EAT) in aortic stenosis (AS), ...
Gophen, M. and Peres, M. (2026) Chill Hours Record: A Sensitive Method for Climate Change Indication. Open Journal of Modern ...
Predictors of Opioid Use among Active-Duty Soldiers Following Postoperative Prescription. Pain Studies and Treatment, 14, ...
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Financial word of the day: Heteroscedasticity — meaning, usage, and why it matters more than ever
Heteroscedasticity describes a situation where risk (variance) changes with the level of a variable. In financial models, ...
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
End-to-end ML pipeline that predicts house sale prices on the Ames Housing dataset using ZenML and MLflow. It ingests raw data, handles missing values and outliers, engineers features ...
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...
Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...
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