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 ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Background: Diabetic peripheral neuropathy (DPN) is a prevalent and highly disabling complication of diabetes mellitus, associated with markedly increased rates of disability and mortality. Timely ...
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 ...
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: This paper presents a novel approach to optimizing vehicle-to-grid (V2G) enhanced energy management in microgrid systems through machine learning-based forecasting. The proposed system ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback