Deep Learning-Based Prediction Modeling of Major Adverse Cardiovascular Events After Liver Transplantation.

Using longitudinal claims data, deep learning models can efficiently predict MACE after LT, assisting clinicians in identifying high-risk candidates for further risk stratification or other management strategies to improve transplant outcomes based on important features identified by the model.