Logistic regression is a statistical method used to model binary outcome variables, such as whether a patient recovers or not, using a set of predictors. There are many competing methods for ...

Pregnancy of uncertain viability affects up to 30% of early pregnancies. Among women presenting with per-vaginal bleeding and absence of a fetal pole, prognosis remains indeterminate. The lack of ...

Introduction The number of children with life-limiting conditions has risen in recent decades, partly due to medical advances ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

Background: Aspiration pneumonia is a serious complication after cardiac surgery, particularly among older patients. Preoperative oral frailty—decline in oral function including poor hygiene and ...

Across the literature, multivariable models for predicting giant cell arteritis diagnoses showed various methodological weaknesses. Multivariable models can aid in the diagnosis of giant cell ...

ABSTRACT: Bipolar disorder is a multifaceted psychiatric illness characterized by unpredictable mood episodes and highly variable treatment responses across individuals. Predicting response to ...

This repository is for downscaling physical fields using multivariate linear regression. Here the model is applied to downscale significant wave height (SWH) in the ...

Ankylosing spondylitis (AS) is an immune-mediated chronic inflammatory disease. When AS is complicated by intervertebral disc degeneration (IVDD), disease complexity increases substantially, often ...