Related Experiment Video
Updated: Jul 28, 2026
Accurate and Simple Measurement of the Pro-inflammatory Cytokine IL-1β using a Whole Blood Stimulation Assay
Published on: March 1, 2011
Development of an explainable AI system using routine clinical parameters for rapid differentiation of inflammatory
Joerg Hoffmann1, Anne Rheude1, Andreas Neubauer1
1Department of Hematology, Oncology and Immunology, Philipps University Marburg, University Hospital Giessen and Marburg, Marburg, Germany.
Introduction:
Inflammatory conditions in patients have various causes and require different treatments. Bacterial infections are treated with antibiotics, while these medications are ineffective against viral infections. Autoimmune diseases and graft-versus-host disease (GVHD) after allogeneic stem cell transplantation, require immunosuppressive therapies such as glucocorticoids, which may be contraindicated in other inflammatory states. In this study, we employ a combination of straightforward blood tests to devise an explainable artificial intelligence (XAI) for distinguishing between bacterial infections, viral infections, and autoimmune diseases/graft-versus-host disease.
Patients And Methods:
We analysed peripheral blood from 80 patients with inflammatory conditions and 38 controls. Complete blood count, CRP analysis, and a rapid flow cytometric test for myeloid activation markers CD169, CD64, and HLA-DR were utilized. A two-step XAI distinguished firstly with C5.0 rules pruned by ABC analysis between controls and inflammatory conditions and secondly between the types of inflammatory conditions with a new bivariate decision tree using the Simpson impurity function.
Results:
Inflammatory conditions were distinguished using an XAI, achieving an overall accuracy of 81.0% (95%CI 72 - 87%). Bacterial infection (N = 30), viral infection (N = 26), and autoimmune diseases/GVHD (N = 24) were differentiated with accuracies of 90.3%, 80.0%, and 79.0%, respectively. The most critical parameter for distinguishing between controls and inflammatory conditions was the expression of CD64 on neutrophils. Monocyte count and expression of CD169 were most crucial for the classification within the inflammatory conditions.
Conclusion:
Treatment decisions for inflammatory conditions can be effectively guided by XAI rules, straightforward to implement and based on promptly acquired blood parameters.
