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

Cardiovascular diseases (CVDs) are a group of heart and blood vesseldisorders that is one of the most serious dangers to human health, and thenumber of such patients is still growing. Early and accurate detection plays akey role in successful treatment and intervention. Electrocardiogram (ECG) isthe gold standard for identifying a variety of cardiovascular abnormalities. Inclinical practices and most of the current research, standard 12-lead ECG ismainly used. However, using a lower number of leads can make ECG more prevalentas it can be conveniently recorded by portable or wearable devices. In thisresearch, we develop a novel deep learning system to accurately identifymultiple cardiovascular abnormalities by using only three ECG leads.

LightX3ECG: A Lightweight and eXplainable Deep Learning System for 3-lead Electrocardiogram Classification