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

Abstract: Faced with high-dimensional expensive optimization problems (HEOPs), existing high-dimensional expensive optimization algorithms (HEOAs) struggle to locate promising areas quickly due to a ...

Abstract: With the innovative application of machine learning neural networks, the problem of feature extraction and dimensionality reduction in big data processing has received extensive attention, ...

1 Rice Research Institute, Guangdong Academy of Agricultural Sciences/Key Laboratory of Genetics and Breeding of High Quality Rice in Southern China (Co-construction by Ministry and Province), ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...

Shanghai, August 21, 2025 — Nuclear energy is widely recognized as one of the most promising clean energy sources for the future, but its safe and efficient use depends critically on the development ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. EncoderMap is a dimensionality reduction method that is tailored for the analysis of ...

Machine learning can enhance ARF outcome predictions but faces challenges like data quality, system heterogeneity, and clinician acceptance. High ARF mortality and mechanical ventilation risks ...