Publication Name	World Journal of Critical Care Medicine
Manuscript ID	102808
Country	Bulgaria

Category	Critical Care Medicine
Manuscript Type	Opinion Review
Article Title	Utilizing artificial intelligence as an arbitrary tool in managing difficult COVID-19 cases in critical care medicine
Manuscript Source	Invited Manuscript
All Author List	Lyubomir Chervenkov, Dimitrina Georgieva Miteva and Tsvetelina Velikova
Funding Agency and Grant Number	Funding Agency Grant Number the European Union-NextGenerationEU, through the National Recovery and Resilience Plan of the Republic of Bulgaria BG-RRP-2.004-0008
Corresponding Author	Lyubomir Chervenkov, Assistant Professor, MD, PhD, Department of Diagnostic Imaging, Medical University Plovdiv, Bul. Vasil Aprilov 15A, Plovdiv 4000, Bulgaria. lyubo.ch@gmail.com
Key Words	Artificial Intelligence; COVID-19; High-resolution computed tomography; Computed tomography; Diagnosis; Treatment; Critical care medicine arbitrary
Core Tip	Coronavirus disease 2019 (COVID-19) presents a range of characteristic patterns and findings on computed tomography (CT) scans that reflect disease progression and severity. Accurate interpretation is crucial for patient management, yet this task is complicated by the variability in radiologists' experience and training. Standardizing CT reporting by grouping findings into distinct categories based on disease stage could improve consistency. However, variability and potential subjectivity persist, highlighting the need for artificial intelligence (AI) support in imaging diagnostics. AI can aid radiologists in achieving more accurate, objective interpretations by identifying, classifying, and quantifying changes, ultimately contributing to a more reliable and standardized approach to diagnosing and managing COVID-19 in critical care settings.
Citation	Chervenkov L, Miteva DG, Velikova T. Utilizing artificial intelligence as an arbitrary tool in managing difficult COVID-19 cases in critical care medicine. World J Crit Care Med 2025; In press

Received	2024-10-31 05:29
Peer-Review Started	2024-10-31 05:29
To Make the First Decision
Return for Revision	2025-03-05 08:16
Revised	2025-03-19 06:06
Second Decision	2025-04-14 02:41
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-04-14 09:00
Articles in Press	2025-04-14 09:00
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	2220-3141(online)
Open Access	This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
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