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Volume 14
Issue 1
10.18683/germs.2024.1419
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GERMS is published by MDPI from Volume 25 Issue 4 (2025). Previous articles were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence, and they are hosted by MDPI on mdpi.com as a courtesy and upon agreement with the former publisher Infection Science Forum S.R.L..
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Review

Implications of Using Artificial Intelligence in the Diagnosis of Sepsis/Sepsis Shock

by
Gabriel-Petre Gorecki
1,2,
Dana-Rodica Tomescu
3,4,
Liana Pleș
5,6,
Anca-Maria Panaitescu
5,7,
Șerban Dragosloveanu
8,9,
Cristian Scheau
10,11,
Romina-Marina Sima
6,*,
Ionuț-Simion Coman
12,13,
Valentin-Titus Grigorean
12,13 and
Daniel Cochior
14,15
1
Department of Anesthesia and Intensive Care, “Titu Maiorescu” University, Faculty of Medicine, 67A Gheorghe Petrașcu Street, 031593 Bucharest, Romania
2
CF2 Clinical Hospital, Department of Anesthesia and Intensive Care, 63 Mărăşti Boulevard, 011464 Bucharest, Romania
3
Department of Anesthesia and Intensive Care, Carol Davila University of Medicine and Pharmacy, 37 Dionisie Lupu Street, 020021 Bucharest, Romania
4
Fundeni Clinical Institute, Department of Anesthesia and Intensive Care, 258 Fundeni Road, 022328 Bucharest, Romania
5
Department of Obstetrics and Gynecology, Carol Davila University of Medicine and Pharmacy, 37 Dionisie Lupu Street, 020021 Bucharest, Romania
6
Department of Obstetrics and Gynecology, “Saint John” Emergency Clinical Hospital, “Bucur” Maternity, 10 Între Gârle Street, 040294 Bucharest, Romania
7
Filantropia Clinical Hospital, Department of Obstetrics and Gynecology, 11-13 Ion Mihalache Boulevard, 011132 Bucharest, Romania
8
Department of Orthopaedics and Traumatology, Carol Davila University of Medicine and Pharmacy, 8 Eroii Sanitari Blvd, 050474 Bucharest, Romania
9
Department of Orthopaedics, “Foișor” Clinical Hospital of Orthopaedics, Traumatology and Osteoarticular TB, 35-37 Ferdinand Blvd, 021382 Bucharest, Romania
10
Department of Physiology, Carol Davila University of Medicine and Pharmacy, 8 Eroii Sanitari Blvd, 050474 Bucharest, Romania
11
Department of Radiology and Medical Imaging, “Foișor” Clinical Hospital of Orthopaedics, Traumatology and Osteoarticular TB, 35-37 Ferdinand Blvd, 021382 Bucharest, Romania
12
Department of General Surgery, Carol Davila University of Medicine and Pharmacy, 37 Dionisie Lupu Street, 020021 Bucharest, Romania
13
“Bagdasar-Arseni” Emergency Clinical Hospital, Department of General Surgery, 12 Berceni Road, 041915 Bucharest, Romania
14
Department of General Surgery, Titu Maiorescu University, Faculty of Medicine, 67A Gheorghe Petrașcu Street, 031593 Bucharest, Romania
15
Monza Clinical Hospital, Department of General Surgery, 27 Tony Bulandra Street, 021967 Bucharest, Romania
 
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Author to whom correspondence should be addressed.
GERMS 2024, 14(1), 77-84; https://doi.org/10.18683/germs.2024.1419
Submission received: 29 February 2024 / Revised: 29 March 2024 / Accepted: 31 March 2024 / Published: 31 March 2024
Versions Notes

Abstract

Introduction: Sepsis and septic shock represent severe pathological states, characterized by the systemic response to infection, which can lead to organ dysfunction and high mortality. Early diagnosis and rapid intervention are crucial for improving survival chances. However, the diagnosis of sepsis is complex due to its nonspecific symptoms and the variability of patient responses to infections. Methods: The objective of this research was to analyze the implications of using artificial intelligence (AI) in the diagnosis of sepsis and septic shock. The research method applied in the analysis of the implications of using artificial intelligence (AI) in the diagnosis of sepsis and septic shock is the literature review. Results: Among the benefits of using AI in the diagnosis of sepsis, it is noted that artificial intelligence can rapidly analyze large volumes of clinical data to identify early signs of sepsis, sometimes even before symptoms become evident to medical staff. AI models can use predictive algorithms to assess the risk of sepsis in patients, allowing for early interventions that can save lives. AI can contribute to the development of personalized treatment plans, adapting to the specific needs of each patient based on their medical history and response to treatment. The use of patient data to train AI models raises concerns regarding data privacy and security. Conclusions: Artificial intelligence has the potential to revolutionize the diagnosis and treatment of sepsis, offering powerful tools for early identification and management of this critical condition. However, to realize this potential, close collaboration between researchers, clinicians, and technology developers is necessary, as well as addressing ethical and implementation challenges.
Keywords: machine learning; clinical decision support systems; biomarkers; outcome prediction; predictive modeling machine learning; clinical decision support systems; biomarkers; outcome prediction; predictive modeling

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MDPI and ACS Style

Gorecki, G.-P.; Tomescu, D.-R.; Pleș, L.; Panaitescu, A.-M.; Dragosloveanu, Ș.; Scheau, C.; Sima, R.-M.; Coman, I.-S.; Grigorean, V.-T.; Cochior, D. Implications of Using Artificial Intelligence in the Diagnosis of Sepsis/Sepsis Shock. GERMS 2024, 14, 77-84. https://doi.org/10.18683/germs.2024.1419

AMA Style

Gorecki G-P, Tomescu D-R, Pleș L, Panaitescu A-M, Dragosloveanu Ș, Scheau C, Sima R-M, Coman I-S, Grigorean V-T, Cochior D. Implications of Using Artificial Intelligence in the Diagnosis of Sepsis/Sepsis Shock. GERMS. 2024; 14(1):77-84. https://doi.org/10.18683/germs.2024.1419

Chicago/Turabian Style

Gorecki, Gabriel-Petre, Dana-Rodica Tomescu, Liana Pleș, Anca-Maria Panaitescu, Șerban Dragosloveanu, Cristian Scheau, Romina-Marina Sima, Ionuț-Simion Coman, Valentin-Titus Grigorean, and Daniel Cochior. 2024. "Implications of Using Artificial Intelligence in the Diagnosis of Sepsis/Sepsis Shock" GERMS 14, no. 1: 77-84. https://doi.org/10.18683/germs.2024.1419

APA Style

Gorecki, G.-P., Tomescu, D.-R., Pleș, L., Panaitescu, A.-M., Dragosloveanu, Ș., Scheau, C., Sima, R.-M., Coman, I.-S., Grigorean, V.-T., & Cochior, D. (2024). Implications of Using Artificial Intelligence in the Diagnosis of Sepsis/Sepsis Shock. GERMS, 14(1), 77-84. https://doi.org/10.18683/germs.2024.1419

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