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

For appropriate treatment, accurate discrimination between seborrheic dermatitis and psoriasis in a timely manner is crucial to avoid complications. However, when they occur on the scalp, differential diagnosis can be challenging using conventional dermascopes. Thus, we employed smartphone-based multispectral imaging and analysis to discriminate between them with high accuracy. A smartphone-based multispectral imaging system, suited for scalp disease diagnosis, was redesigned. We compared the outcomes obtained using machine learning-based and conventional spectral classification methods to achieve better discrimination. The results demonstrated that smartphone-based multispectral imaging and analysis has great potential for discriminating between these diseases.

Smartphone-based multispectral imaging and machine-learning based analysis for discrimination between seborrheic dermatitis and psoriasis on the scalp