A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), the most common ...

Cambridge AI startup Theia Insights has raised $8M to scale its dynamic company classification platform for financial markets ...

Passive Brain-Computer Interfaces (pBCIs) have shown significant advancements in recent years, indicating their readiness for ...

Researchers have optimized a headspace sorptive extraction (HSSE) method coupled with gas chromatography-mass spectrometry ...

This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within ...

Objective To estimate the prevalence of potential overtreatment of type 2 diabetes mellitus (T2DM) among older adults and to develop and compare predictive models to identify patient and physician ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Monitoring of natural resources is a major challenge that remote sensing tools help to facilitate. The Sissili province in Burkina Faso is a territory that includes significant areas dedicated for the ...

Abstract: Urban vegetation classification is challenging due to the heterogeneous nature of urban environments. Accurate mapping of urban vegetation, which plays a crucial role in regulating ...

Abstract: This study presents a comprehensive benchmarking of 33 machine learning (ML) algorithms for bearing fault classification using vibration data, with a focus on real-world deployment in ...