From visualization to prediction: Dissecting metabolic heterogeneity with DDRTree
The discriminative dimensionality reduction tree (DDRTree) framework provides a powerful approach to unravel metabolic heterogeneity and delineate clinically relevant subtypes. In this issue, Qiu et al.<sup>1</sup> and Jia et al.<sup>2</sup> apply it to type 2 diabetes and obesity, identifying subtypes with distinct risk profiles.
Authors
- Yonghua Yu
- Hong Lin (ORCID: https://orcid.org/0000-0001-5860-4358)
Institutions
- Ruijin Hospital (CN)
Publication Details
- Journal
- Cell Reports Medicine
- Published
- 2025-11-01
- DOI
- https://doi.org/10.1016/j.xcrm.2025.102377
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00