The XGBoost-based approach demonstrated robust external validation across multiple centers, supporting clinical adoption to guide personalized treatment decisions.

Using the XGBoost algorithm, we developed a classifier incorporating nine genes (ARHGAP9, CADM1, CPE, DUSP3, FGFR1, GALNT3, IGF2BP3, KIF26A, ZFP3). In our internal cohort, the classifier exhibited ...

A machine learning-based model can predict 30-day in-hospital mortality among patients with asthma in the ICU.

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 ...

Dutch scientists have developed a PV forecasting method that uses the XGBoost algorithm. They claim their approach predicts electricity generation levels an hour ahead for big fleets of ...

July 31, 2019-- Machine learning algorithms are extremely computationally intensive and time consuming when they must be trained on large amounts of data. Typical processors are not optimized for ...

The patent abstract shows that this invention relates to a multi-level review method and device based on a credit model for railway supply chain financial business. The method includes: constructing a ...