A hybrid model combining LM, GA, and BP neural networks improves TCM's diagnostic accuracy for IPF, achieving 81.22% ...

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 ...