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

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

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

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

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

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 ...

Food production facilities, particularly those in continuous, high-throughput environments such as sausage manufacturing, face a unique combination of operational challenges. Equipment must operate ...

How does Luhn’s algorithm know when your fingers fumble? Every digit in a credit card number contributes a one-digit number to the final sum in the algorithm.

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

The core of this patent lies in constructing a machine learning database, using design parameters of seismic isolation bearings as input data, and bridge target response data as output data.