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 Plus annual

Presents the access of premium content as premium feature

Premium Content

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 annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Diabetes mellitus is a disease of high public health relevance. To estimate the temporal development of prevalence, routine data of statutory health insurances (SHI) are being increasingly used. However, these data are primarily collected for billing purposes and the case definition of specific diseases remains challenging. In this study, we present an algorithm for differentiation of diabetes types analyzing SHI routine data.

Algorithmus zur Unterscheidung von Diabetes mellitus Typ 1 und Typ 2 bei der Analyse von Routinedaten