Prediction of influenza virus infection based on deep learning and peripheral blood proteomics: A diagnostic study.

ABSTRACT:

Introduction

Influenza viruses cause seasonal epidemics almost every year, and it is difficult to diagnose quickly and accurately. Machine learning and peripheral blood protein omics have brought new ideas to the research of clinical markers.

Objectives

Prediction of key molecular marker of influenza virus infection by the established machine learning model and peripheral blood protein omics.

Methods

This study used the testing data of 850 patients (including influenza, COVID-19 and mixed infections) and 265 healthy individuals, to establish and validate a diagnostic prediction model for influenza infection and verified the potential value of this model in the differential diagnosis of influenza, COVID-19 and healthy people.

Results

The overall analysis showed

SUBMITTER: Zhou Y 

PROVIDER: S-EPMC12766177 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature