ascopubs.org

Prediction of Patients With High-Risk Osteosarcoma on the Basis of XGBoost Algorithm Using Transcriptome and Methylation Data From SGH-OS Cohort

Benefits of Combining Circulating Tumor DNA With Tissue and Longitudinal Circulating Tumor DNA Genotyping in Advanced Solid Tumors: SCRUM-Japan MONSTAR-SCREEN-1 Study Osteosarcoma (OS) is the most ...
pv magazine International

Machine learning method to identify residential PV adopters, reduce soft costs

An international research team has utilized a machine learning algorithm known as XGBoost (eXtreme Gradient Boosting) to predict PV adoption among homeowners. This algorithm consists of a distributed ...
techtimes

Anodot, oneDAL Optimize Anomaly Detection Services

Using Intel® hardware, Intel® Integrated Performance Primitives (Intel® IPP) and Intel® oneAPI Data Analytics Library (oneDAL), Anodot improved the performance of its autocorrelation function (ACF) ...
The American Journal of Managed Care

Mortality Prediction Models Perform Poorly in Pneumonic COPD Exacerbations

Two common models, the CURB-65 and BAP-65, had low predictive value in determining which patients with pneumonic chronic obstructive pulmonary disease would not survive. Common models used to predict ...