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

Bankruptcy prediction has traditionally relied on statistical approaches such as Altman’s Z-score, which use financial ratios ...

A new machine learning model developed by Mount Sinai researchers could reduce overcrowding in emergency departments, improve staff efficiencies and boost patient outcomes by informing ED ...

Engineered nanozymes and explainable machine learning enable sensitive bacterial detection across complex conditions. The system uses three distinct signals and delivers transparent, verifiable ...

Background Machine learning based on clinical characteristics has the potential to predict coronary CT angiography (CCTA) findings and help guide resource utilisation.Methods From the SCOT-HEART ...

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

The conversion of carbon dioxide into clean fuels is regarded as an important route toward carbon neutrality. CO2 methanation ...

Government procurement contracts can be complicated, with extensive risk analysis and compliance reviews. The traditional ...

The core of big data models lies in the synergy of algorithm innovation, computational power support, and data governance to ...