Leveraging Machine Learning to Enhance Postoperative Risk Assessment in Coronary Artery Bypass Grafting Patients with Unprotected Left Main Disease - A Retrospective Cohort Study Ahmed Elmahrouk , Amin Daoulah , Prashanth Panduranga , Rajesh Rajan , Ahmed Jamjoom , Omar Kanbr , Badr Alzahrani , Mohammed A. Qutub , Nooraldaem Yousif , Tarique Shahzad Chachar , Youssef Elmahrouk , Ali Alshehri , Taher Hassan , Wael Tawfik , Kamel Hazaa Haider , Abdulwali Abohasan , Adel N. Alqublan , Abdulrahman M. Alqahtani , Mohamed Ajaz Ghani , Faisal Omar M. Al Nasser , Wael Almahmeed , Ahmed A. Ghonim , Shahrukh Hashmani , Mohammed Alshehri , Abdelmaksoud Elganady , Abeer M. Shawky , Adnan Fathey Hussien , Seraj Abualnaja , Taha H. Noor , Ibrahim A. M. Abdulhabeeb , Levent Ozdemir , Wael Refaat , Hameedullah M. Kazim , Ehab Selim , Issam Altnji , Ahmed M. Ibrahim , Abdullah Alquaid , Amr A. Arafat INTERNATIONAL JOURNAL OF SURGERY（2024）
Key words
coronary artery bypass grafting, explainable artificial intelligence, left main coronary artery, machine learning
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