1. The integration of decision tree models into clinical practice can assist surgeons in preoperative planning and decision-making. These models can provide risk assessment by analyzing preoperative patient characteristics and predicting the likelihood of massive bleeding in pancreatic surgery. The operation team can use this kind of prediction for the intended client and plan to approach the required precautions and preparations accordingly. But the decision tree model should only be used as a tool to support the clinical decision since the expertise of the operation team is more valuable.
2. Using the decision tree model in a clinical setting has many benefits for risk identification, personalized treatment and the decision-making process. Since it can identify high-risk patients, specific interventions can be addressed to improve outcomes and patient satisfaction. But there are some limitations with the model which include data availability and quality, model complexity and interpretability. It also needs regular updates to be used effectively. Thus, it is important to validate and interpret the model’s predictions for every patient and clinical expertise.