Machine Learning to Predict Outcomes of Endovascular Intervention for Patients With PAD
Ben Li,
Blair E. Warren,
Naomi Eisenberg
et al.
Abstract:ImportanceEndovascular intervention for peripheral artery disease (PAD) carries nonnegligible perioperative risks; however, outcome prediction tools are limited.ObjectiveTo develop machine learning (ML) algorithms that can predict outcomes following endovascular intervention for PAD.Design, Setting, and ParticipantsThis prognostic study included patients who underwent endovascular intervention for PAD between January 1, 2004, and July 5, 2023, with 1 year of follow-up. Data were obtained from the Vascular Qual… Show more
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