http://www.aging.ai. The ensemble approach may facilitate integration of multi-modal data linked to chronological age and sex that may lead to simple, minimally invasive, and affordable methods of tracking integrated biomarkers of aging in humans and performing cross-species feature importance analysis." name="description"> Deep biomarkers of human aging: Application of deep neural networks to biomarker development - Figure F4 | Aging
Research Paper Volume 8, Issue 5 pp 1021—1030

Deep biomarkers of human aging: Application of deep neural networks to biomarker development

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Figure 4. Comparison of sub-models for stacking ensemble and evaluation of filling strategies. (A) ElasticNet model has the higher epsilon-prediction accuracy among the stacking models. (B) ElasticNet is the best model for stacking from the point of R2 statistics. (C) Median filling strategy has higher epsilon-prediction accuracy than other strategies. Median filling strategy shows 64,5 % epsilon accuracy within 10 years frame. (D) Median filling strategy is better from the point of R2 statistics.