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

Ioana Hălmaciu¹, Anca Meda Văsieșiu², Andrei Manea^1,3

¹Department of Radiology, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, Targu Mures, Romania.

Journal of Critical Care Medicine (Universitatea De Medicina Si Farmacie Din Targu-Mures)

|August 6, 2025

Summary

Artificial intelligence analysis of COVID-19 pneumonia CT scans, combined with inflammatory markers like neutrophil-lymphocyte ratio (NLR), accurately predicts patient survival rates. Higher inflammation and lung opacity scores correlate with decreased survival.

Keywords:

COVID-19 SARS-CoV-2 artificial intelligence inflammatory markers interleukin 6

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Area of Science:

Radiology
Pulmonology
Artificial Intelligence in Medicine

Background:

COVID-19 pneumonia presents with diverse symptoms, from mild to severe.
Chest CT is vital for assessing pulmonary lesions and disease severity.
AI tools aid in rapid diagnosis and quantitative lesion evaluation for COVID-19.

Purpose of the Study:

To correlate lung lesions on CT scans with biological inflammatory markers.
To establish the survival rate among patients with COVID-19 pneumonia.
To evaluate the role of AI in assessing COVID-19 pneumonia severity.

Main Methods:

Retrospective analysis of 120 moderate to severe COVID-19 pneumonia patients.
Chest CT scans analyzed by radiologists and AI post-processing software.
Assessment of inflammatory markers including neutrophil-lymphocyte ratio (NLR) and interleukin-6.

Main Results:

Strong correlations found between inflammatory markers, interleukin-6, and AI-derived CT severity scores (e.g., NLR r=0.851).
Elevated inflammatory markers and lung opacity scores correlated with reduced survival.
Crazy paving pattern on CT associated with increased mortality risk (OR=2.89).

Conclusions:

AI-based chest CT analysis is crucial for evaluating COVID-19 pneumonia.
Combining AI CT analysis with inflammatory markers offers a reliable, objective assessment.
This integrated approach enhances diagnostic accuracy and prognostic evaluation for COVID-19 patients.