Whole-blood DNA-methylation score for cardiovascular risk. The paper's final cross-study learner stacks cohort-specific elastic-net Cox models; the packaged pyaging implementation is a 235-CpG linear score followed by a sigmoid.
Predicts
cardiovascular disease risk
Species
Homo sapiens
Tissue
whole blood
Data type
DNA methylation
Model type
elastic net Cox ensemble
Year
2020
Use with pyaging
import pyaging as pya
pya.pred.predict_age(adata, ["cvdwesterman"])
Westerman, K. et al. Epigenomic assessment of cardiovascular disease risk and interactions with traditional risk metrics. Journal of the American Heart Association 9, e015299 (2020).
cvdwesterman huggingface.co is an AI model on huggingface.co that provides cvdwesterman's model effect (), which can be used instantly with this pyaging cvdwesterman model. huggingface.co supports a free trial of the cvdwesterman model, and also provides paid use of the cvdwesterman. Support call cvdwesterman model through api, including Node.js, Python, http.
cvdwesterman huggingface.co is an online trial and call api platform, which integrates cvdwesterman's modeling effects, including api services, and provides a free online trial of cvdwesterman, you can try cvdwesterman online for free by clicking the link below.
pyaging cvdwesterman online free url in huggingface.co:
cvdwesterman is an open source model from GitHub that offers a free installation service, and any user can find cvdwesterman on GitHub to install. At the same time, huggingface.co provides the effect of cvdwesterman install, users can directly use cvdwesterman installed effect in huggingface.co for debugging and trial. It also supports api for free installation.