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

The development of models for Electronic Health Record data is an area ofactive research featuring a small number of public benchmark data sets.Researchers typically write custom data processing code but this hindersreproducibility and can introduce errors. The Python package torchtime providesreproducible implementations of commonly used PhysioNet and UEA & UCR timeseries classification repository data sets for PyTorch. Features are providedfor working with irregularly sampled and partially observed time series ofunequal length. It aims to simplify access to PhysioNet data and enable faircomparisons of models in this exciting area of research.

Benchmark time series data sets for PyTorch -- the torchtime package