Predicting Outcomes Following Lower Extremity Open Revascularization Using Machine Learning

This article discusses the use of machine learning in predicting peri-operative complications in patients undergoing lower extremity open revascularization. The study utilized data from the ACS NSQIP database and found that developing ML algorithms specific to this surgical population can improve predictive performance. The study was conducted in accordance with ethical guidelines and reported based on the TRIPOD statement.