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

New statistical methods were employed to improve the ability to distinguishbenign from malignant breast tissue ex vivo in a recent study. The ultimatelyaim was to improve the intraoperative assessment of positive tumour margins inbreast-conserving surgery (BCS), potentially reducing patient re-operationrates. A multivariate Bayesian classifier was applied to the waveform samplesproduced by a Terahertz Pulsed Imaging (TPI) handheld probe system in order todiscriminate tumour from benign breast tissue, obtaining a sensitivity of 96%and specificity of 95%.  We compare these results to traditional and to state-of-the-art methods fordetermining resection margins. Given the general nature of the classifier, itis expected that this method can be applied to other tumour types whereresection margins are also critical.

Improved resection margins in breast-conserving surgery using Terahertz Pulsed imaging data