ascopubs.org

Development of Machine Learning Algorithms Incorporating Electronic Health Record Data, Patient-Reported Outcomes, or Both to Predict Mortality for Outpatients With Cancer

shinyOPTIK, a User-Friendly R Shiny Application for Visualizing Cancer Risk Factors and Mortality Across the University of Kansas Cancer Center Catchment Area We trained and validated two-phase ML ...
The American Journal of Managed Care

28-Day Mortality Predicted by Machine Learning in Patients With CRC

Critically ill older patients with colorectal cancer (CRC) had their 28-day mortality predicted using machine learning algorithms. Machine learning algorithms were able to be used to predict the ...
Semiconductor Engineering

Using Machine Learning To Automate Debug Of Simulation Regression Results

Regression failure debug is usually a manual process wherein verification engineers debug hundreds, if not thousands of failing tests. Machine learning (ML) technologies have enabled an automated ...
EurekAlert!

Smart solutions for sustainable energy: Machine learning powers biochar production from aquatic biomass

The increasing global demand for sustainable energy and carbon materials, alongside pressing environmental concerns, necessitates innovative approaches to resource management. Biomass, a versatile ...