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Artificial intelligence algorithms based approach in evaluating COVID-19 patients and management Cover

Artificial intelligence algorithms based approach in evaluating COVID-19 patients and management

Open Access
|Jul 2025

Abstract

Introduction

COVID-19 pneumonia manifests with a wide range of clinical symptoms, from minor flu-like signs to multi-organ failure. Chest computed tomography (CT) is the most effective imaging method for assessing the extent of the pulmonary lesions and correlates with disease severity. Increased workloads during the COVID-19 pandemic led to the development of various artificial intelligence tools to enable quicker diagnoses and quantitative evaluations of the lesions.

Aim of the study

This study aims to analyse the correlation between lung lesions identified on CT scans and the biological inflammatory markers assessed, to establish the survival rate among patients.

Methods

This retrospective study included 120 patients diagnosed with moderate to severe COVID-19 pneumonia who were admitted to the intensive care unit and the internal medicine department between September 2020 and October 2021. Each patient underwent a chest CT scan, which was subsequently analysed by two radiologists and an AI post-processing software. On the same day, blood was collected from the patients to determine inflammatory markers. The markers analysed in this study include the neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio, platelet-lymphocyte ratio, systemic immune-inflammatory index, systemic inflammation response index, systemic inflammation index, and serum interleukin-6 value.

Results

There were strong and very strong correlations between the derived inflammatory markers, interleukin-6, and the CT severity scores obtained by the AI algorithm (r=0.851, p<0.001 in the case of NLR). Higher values of the inflammatory markers and high lung opacity scores correlated with a decreased survival rate. Crazy paving was also associated with an increased risk of mortality (OR=2.89, p=0.006).

Conclusions

AI-based chest CT analysis plays a crucial role in assessing patients with COVID-19 pneumonia. When combined with inflammatory markers, it provides a reliable and objective method for evaluating COVID-19 pneumonia, enhancing the accuracy of diagnosis.

DOI: https://doi.org/10.2478/jccm-2025-0032 | Journal eISSN: 2393-1817 | Journal ISSN: 2393-1809
Language: English
Page range: 247 - 256
Submitted on: May 15, 2025
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Accepted on: Jul 4, 2025
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Published on: Jul 31, 2025
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2025 Ioana Hălmaciu, Anca Meda Văsieșiu, Andrei Manea, Andrei Dragomir, Ioana Tripon, Vlad Vunvulea, Cristian Boeriu, Andrea Rus, Minodora Dobreanu, published by University of Medicine, Pharmacy, Science and Technology of Targu Mures
This work is licensed under the Creative Commons Attribution 4.0 License.