English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Additionally to the extensive use in clinical medicine, biological age (BA)in legal medicine is used to assess unknown chronological age (CA) inapplications where identification documents are not available. Automaticmethods for age estimation proposed in the literature are predicting pointestimates, which can be misleading without the quantification of predictiveuncertainty. In our multi-factorial age estimation method from MRI data, weused the Variational Inference approach to estimate the uncertainty of aBayesian CNN model. Distinguishing model uncertainty from data uncertainty, weinterpreted data uncertainty as biological variation, i.e. the range ofpossible CA of subjects having the same BA.

Variational Inference and Bayesian CNNs for Uncertainty Estimation in Multi-Factorial Bone Age Prediction