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

From 2017 to 2019 the Text REtrieval Conference (TREC) held a challenge taskon precision medicine using documents from medical publications (PubMed) andclinical trials. Despite lots of performance measurements carried out in theseevaluation campaigns, the scientific community is still pretty unsure about theimpact individual system features and their weights have on the overall systemperformance. In order to overcome this explanatory gap, we first determinedoptimal feature configurations using the Sequential Model-based AlgorithmConfiguration (SMAC) program and applied its output to a BM25-based searchengine. We then ran an ablation study to systematically assess the individualcontributions of relevant system features: BM25 parameters, query type andweighting schema, query expansion, stop word filtering, and keyword boosting.For evaluation, we employed the gold standard data from the three TREC-PMinstallments to evaluate the effectiveness of different features using thecommonly shared infNDCG metric.

What Makes a Top-Performing Precision Medicine Search Engine? Tracing Main System Features in a Systematic Way