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 F1 | 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 1. Project pipeline. Laboratory blood biochemistry data sets were normalized and cleaned of outliers and some abnormal markers. For biological age prediction, 21 different DNNs with different parameters were combined in ensemble based on ElasticNet model. For biological sex prediction, single DNN were trained.