Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

Abstract: A precise change detection in the multi-temporal optical images is considered as a crucial task. Although a variety of machine learning-based change detection algorithms have been proposed ...

Researchers at Beijing Normal University used advanced machine learning and satellite imagery to map forest management ...

For each league, the application computes several statistics (features) about the teams, including their form, the performance of the last N matches, etc. The stats are computed for both the home team ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Objective: To develop an auxiliary diagnostic tool for schizophrenia based on multiple test variables using different machine learning algorithms. Results: Arg, TP, ALP, HDL, UA, and LDL were ...

ABSTRACT: Accurate land cover classification is essential for environmental monitoring, urban planning, and resource management. Conventional classifiers trained on raw spectral bands are often ...

With climate change posing an unprecedented global challenge, the demand for environmentally friendly solvents in green chemical processes and carbon dioxide capture has surged. Ionic liquids (ILs) ...

Abstract: By evaluating intricate datasets to maximize plant growth, boost yields, and advance sustainability, smart agriculture—powered by Random Forest machine learning—is transforming botany.

ABSTRACT: Meditation offers a controlled behavioral context for probing attention, arousal, and self-regulation. Rather than positioning the present work as a discovery of novel neural signatures, we ...