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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Adoption of machine learning models in healthcare requires end users' trustin the system. Models that provide additional supportive evidence for theirpredictions promise to facilitate adoption. We define consistent evidence to beboth compatible and sufficient with respect to model predictions. We proposemeasures of model inconsistency and regularizers that promote more consistentevidence. We demonstrate our ideas in the context of edema severity gradingfrom chest radiographs. We demonstrate empirically that consistent modelsprovide competitive performance while supporting interpretation.

Image Classification with Consistent Supporting Evidence