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

In this study, the combination of a developing data mining technique calledstatistical decision tree analysis method and Raman spectroscopy was proposedto differentiate human normal leukocytes from malignant tumor cells.Statistical results obtained indicate this method possesses an admirableperformance of a mean classification accuracy of 94.43% on the one hand, baseadenine and amide I are recognized as potential characterizations of main- andsubintrinsic biological difference in between on the other hand. Moreover,these certain Raman bands reflecting intrinsic physiological differences can bedirectionally extracted from whole fingerprint spectra and then provide a fastand accurate manipulation for spectrum identification.

Intrinsic feature between malignant tumor cells and human normal leukocytes with statistical decision tree analysis via Raman spectroscopy