[HTML][HTML] Privacy-preserving decentralized learning methods for biomedical applications
In recent years, decentralized machine learning has emerged as a significant advancement
in biomedical applications, offering robust solutions for data privacy, security, and …
in biomedical applications, offering robust solutions for data privacy, security, and …
Artificial Intelligence for Central Dogma-Centric Multi-Omics: Challenges and Breakthroughs
L Xin, C Huang, H Li, S Huang, Y Feng, Z Kong… - arXiv preprint arXiv …, 2024 - arxiv.org
With the rapid development of high-throughput sequencing platforms, an increasing number
of omics technologies, such as genomics, metabolomics, and transcriptomics, are being …
of omics technologies, such as genomics, metabolomics, and transcriptomics, are being …
Feature graphs for interpretable unsupervised tree ensembles: centrality, interaction, and application in disease subtyping
Interpretable machine learning has emerged as central in leveraging artificial intelligence
within high-stakes domains such as healthcare, where understanding the rationale behind …
within high-stakes domains such as healthcare, where understanding the rationale behind …