IEEE

Machine Learning and Data Science in Social Sciences: Methods, Applications, and Future Directions

Abstract: Artificial intelligence (AI) is transforming social science research by enabling scalable data analysis, predictive modeling, and causal inference, thereby reshaping the methodological ...
Frontiers

Modeling, Machine Learning, Bioinformatics and Multi-omics Data in Soil Science

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

WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning

Beijing, Jan. 05, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning ...
IEEE

An Improved Bagging of Machine Learning Algorithms to Predict Motif Structures From Protein-Protein Interaction Networks

Abstract: Protein-protein interaction (PPI) networks play a vital role in the functional organization of cellular systems. Recurring subgraph patterns with these networks, known as motif structures, ...