SurgiCut-AI: an AI-driven tool for predicting surgical site infections following ventral hernia repair using pre- and intra-operative parameters
- 01.12.2026
- Original Article
Erschienen in:
- Verfasst von
- Rijhul Lahariya
- Ashesh Kumar Jha
- Mainak Sinha
- Prashant Kumar Singh
- Shiv Shankar Paswan
- Manasi Manasvi
- Manoj Kumar
- Erschienen in
- Hernia | Ausgabe 1/2026
Abstract
Purpose
Surgical Site Infection (SSI) is the common consequence of hernia surgery. This study aimed to develop an artificial intelligence (AI)-driven predictive model for SSI following open ventral hernia repair using pre- and intra-operative parameters for early detection.
Methods
A prospective analysis of ventral hernia patients was conducted. Demographic, pre-operative and intra-operative parameters were collected. Feature selection using Recursive Feature Elimination (RFE) identified key predictors. Five models, eXtreme Gradient Boosting (XGBoost), logistic regression, support vector machine (SVM), Adaptive Boosting and random forest (RF), were trained and validated.
Results
Among 253 patients, 22 were SSI-positive. RF demonstrated the highest predictive power (area under receiver operating characteristic curve = 0.82) and diagnostic odds ratio (DOR = 55). Seven key predictors were identified: defect size area, HbA1c, lymphocytes, neutrophil-to-lymphocyte ratio, blood loss (ml), platelet count and serum albumin. Decision curve analysis showed an estimated risk stratification at an 8.3% cutoff “https://surgicut-ai.netlify.app/”.
Conclusion
The model’s high accuracy supports its potential for clinical decision-making. External validation is required for real-world application. Integrating this AI model into bedside tools may enhance SSI prevention, especially in resource-limited settings.
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- Titel
- SurgiCut-AI: an AI-driven tool for predicting surgical site infections following ventral hernia repair using pre- and intra-operative parameters
- Verfasst von
-
Rijhul Lahariya
Ashesh Kumar Jha
Mainak Sinha
Prashant Kumar Singh
Shiv Shankar Paswan
Manasi Manasvi
Manoj Kumar
- Publikationsdatum
- 01.12.2026
- Verlag
- Springer Paris
- Erschienen in
-
Hernia / Ausgabe 1/2026
Print ISSN: 1265-4906
Elektronische ISSN: 1248-9204 - DOI
- https://doi.org/10.1007/s10029-025-03498-2
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