Machine learning of flow cytometry data reveals the delayed innate immune responses correlate with the severity of COVID-19.

ABSTRACT:

Introduction

The COVID-19 pandemic has posed a major burden on healthcare and economic systems across the globe for over 3 years. Even though vaccines are available, the pathogenesis is still unclear. Multiple studies have indicated heterogeneity of immune responses to SARS-CoV-2, and potentially distinct patient immune types that might be related to disease features. However, those conclusions are mainly inferred by comparing the differences of pathological features between moderate and severe patients, some immunological features may be subjectively overlooked.

Methods

In this study, the relevance scores(RS), reflecting which features play a more critical role in the decision-making process, between immunological features and the COVID-19 severity are objectively calculate

SUBMITTER: Zhu J 

PROVIDER: S-EPMC9951775 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature