Do machine learning models outperform regression-based models for the prediction of postoperative surgical site infections?
Current machine learning models for predicting surgical site infections do not outperform traditional regression models and suffer from high risk of bias and lack of external validation.
A multitude of ML models for the prediction of SSIs are available, with large variability in performance. However, most models lacked external validation, performance was reported limitedly, and the risk of bias was high. In studies describing both ML models and regression-based models, one modelling method did not outperform the other.
Boekel et al. (2024) studied this question.