A hybrid model combining LM, GA, and BP neural networks improves TCM's diagnostic accuracy for IPF, achieving 81.22% classification accuracy. Feature screening using mean impact value (MIV) enhances ...

This new article publication from Acta Pharmaceutica Sinica B, discusses establishment of interpretable cytotoxicity prediction models using machine learning analysis of transcriptome features.

Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...

Interpretable Machine Learning Framework for Biomass–Plastic Co-gasification. This graphical workflow illustrates the development of an interpretable machine learning framework to predict syngas ...

The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to ...