Progressive observation of Covid-19 vaccination effects on skin-cellular structures by use of Intelligent Laser Speckle Classification (ILSC)

TL;DR

This study uses Intelligent Laser Speckle Classification (ILSC) to monitor skin cellular changes due to Covid-19 vaccination, successfully distinguishing between different vaccination statuses and tracking skin alterations over time.

Contribution

The paper introduces a novel application of ILSC combined with Bayesian networks to classify and observe skin cellular changes related to Covid-19 vaccination.

Findings

ILSC can differentiate vaccinated from non-vaccinated skin.

The technique detects progressive skin cellular changes over a month.

Successful classification of early and late vaccinated individuals.

Abstract

We have made a progressive observation of Covid-19 Astra Zeneca Vaccination effect on Skin cellular network and properties by use of well established Intelligent Laser Speckle Classification (ILSC) image based technique and managed to distinguish between three different subjects groups via their laser speckle skin image samplings such as early-vaccinated, late-vaccinated and non-vaccinated individuals. The results have proven that the ILSC technique in association with the optimised Bayesian network is capable of classifying skin changes of vaccinated and non-vaccinated individuals and also of detecting progressive development made on skin cellular properties for a month period.