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 volume of stroke lesion is the gold standard for predicting the clinicaloutcome of stroke patients. However, the presence of stroke lesion may causeneural disruptions to other brain regions, and these potentially damagedregions may affect the clinical outcome of stroke patients. In this paper, weintroduce the tractographic feature to capture these potentially damagedregions and predict the modified Rankin Scale (mRS), which is a widely usedoutcome measure in stroke clinical trials. The tractographic feature is builtfrom the stroke lesion and average connectome information from a group ofnormal subjects. The tractographic feature takes into account differentfunctional regions that may be affected by the stroke, thus complementing thecommonly used stroke volume features. The proposed tractographic feature istested on a public stroke benchmark Ischemic Stroke Lesion Segmentation 2017and achieves higher accuracy than the stroke volume and the state-of-the-artfeature on predicting the mRS grades of stroke patients. In addition, thetractographic feature also yields a lower average absolute error than thecommonly used stroke volume feature.

Predicting Clinical Outcome of Stroke Patients with Tractographic Feature