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The Role of the Fibronectin Synergy Site for Skin Wound Healing
 
 
Article

Explainable Artificial Intelligence Helps in Understanding the Effect of Fibronectin on Survival of Sepsis

1
Department of Chemistry and Immunochemistry, Wroclaw Medical University, M. Sklodowskiej-Curie 48/50, 50-369 Wroclaw, Poland
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Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, 02-097 Warsaw, Poland
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Faculty of Mathematics and Information Science, Warsaw University of Technology, 00-662 Warszawa, Poland
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Clinical Department of Anesthesiology and Intensive Therapy, Wroclaw Medical University, Borowska 213, 50-556 Wroclaw, Poland
*
Author to whom correspondence should be addressed.
Academic Editor: Maria Mitsi
Cells 2022, 11(15), 2433; https://doi.org/10.3390/cells11152433
Received: 9 June 2022 / Revised: 30 July 2022 / Accepted: 3 August 2022 / Published: 5 August 2022
(This article belongs to the Special Issue Fibronectin in Health and Diseases 2022)
Fibronectin (FN) plays an essential role in the host’s response to infection. In previous studies, a significant decrease in the FN level was observed in sepsis; however, it has not been clearly elucidated how this parameter affects the patient’s survival. To better understand the relationship between FN and survival, we utilized innovative approaches from the field of explainable machine learning, including local explanations (Break Down, Shapley Additive Values, Ceteris Paribus), to understand the contribution of FN to predicting individual patient survival. The methodology provides new opportunities to personalize informative predictions for patients. The results showed that the most important indicators for predicting survival in sepsis were INR, FN, age, and the APACHE II score. ROC curve analysis showed that the model’s successful classification rate was 0.92, its sensitivity was 0.92, its positive predictive value was 0.76, and its accuracy was 0.79. To illustrate these possibilities, we have developed and shared a web-based risk calculator for exploring individual patient risk. The web application can be continuously updated with new data in order to further improve the model. View Full-Text
Keywords: sepsis; fibronectin; biomarkers; survival prediction; artificial intelligence models sepsis; fibronectin; biomarkers; survival prediction; artificial intelligence models
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MDPI and ACS Style

Lemańska-Perek, A.; Krzyżanowska-Gołąb, D.; Kobylińska, K.; Biecek, P.; Skalec, T.; Tyszko, M.; Gozdzik, W.; Adamik, B. Explainable Artificial Intelligence Helps in Understanding the Effect of Fibronectin on Survival of Sepsis. Cells 2022, 11, 2433. https://doi.org/10.3390/cells11152433

AMA Style

Lemańska-Perek A, Krzyżanowska-Gołąb D, Kobylińska K, Biecek P, Skalec T, Tyszko M, Gozdzik W, Adamik B. Explainable Artificial Intelligence Helps in Understanding the Effect of Fibronectin on Survival of Sepsis. Cells. 2022; 11(15):2433. https://doi.org/10.3390/cells11152433

Chicago/Turabian Style

Lemańska-Perek, Anna, Dorota Krzyżanowska-Gołąb, Katarzyna Kobylińska, Przemysław Biecek, Tomasz Skalec, Maciej Tyszko, Waldemar Gozdzik, and Barbara Adamik. 2022. "Explainable Artificial Intelligence Helps in Understanding the Effect of Fibronectin on Survival of Sepsis" Cells 11, no. 15: 2433. https://doi.org/10.3390/cells11152433

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