AI Medical Compendium Journal:
Statistics in biosciences

Showing 1 to 4 of 4 articles

Considerations and targeted approaches to identifying bad actors in exposure mixtures.

Statistics in biosciences
Variable importance is a key statistical issue in exposure mixtures, as it allows a ranking of exposures as potential targets for intervention, and helps to identify bad actors within a mixture. In settings where mixtures have many constituents or hi...

Likelihood-Based Methods for Assessing Principal Surrogate Endpoints in Vaccine Trials.

Statistics in biosciences
When evaluating principal surrogate biomarkers in vaccine trials, missingness in potential outcomes requires prediction using auxiliary variables and/or augmented study design with a close-out placebo vaccination (CPV) component. The estimated likeli...

Classification of Large-Scale Remote Sensing Images for Automatic Identification of Health Hazards: Smoke Detection Using an Autologistic Regression Classifier.

Statistics in biosciences
Remote sensing images from Earth-orbiting satellites are a potentially rich data source for monitoring and cataloguing atmospheric health hazards that cover large geographic regions. A method is proposed for classifying such images into hazard and no...

A LASSO Method to Identify Protein Signature Predicting Post-transplant Renal Graft Survival.

Statistics in biosciences
Identifying novel biomarkers to predict renal graft survival is important in post-transplant clinical practice. Serum creatinine, currently the most popular surrogate biomarker, offers limited information of the underlying allograft profiles. It is k...