Improving Quality in Cardiothoracic Surgery: Exploiting the Untapped Potential of Machine Learning

Affiliations

¹ Saïd Business School, Oxford University, Oxford, United Kingdom. Electronic address: agni.orfanoudaki@sbs.ox.ac.uk.
² Department of Cardiovascular Surgery, Mayo Clinic, Rochester, Minnesota.
³ Division of Cardiac Surgery, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
⁴ Department of Cardiovascular and Thoracic Surgery, West Virginia University, Morgantown, West Virginia.
⁵ Division of Cardiothoracic Surgery, Emory University School of Medicine Atlanta, Georgia.
⁶ The Society of Thoracic Surgeons, Chicago, Illinois.
⁷ Department of Cardiac Surgery, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California.
⁸ Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts.

Editorial

Agni Orfanoudaki et al. Ann Thorac Surg. 2022 Dec.

. 2022 Dec;114(6):1995-2000.

doi: 10.1016/j.athoracsur.2022.06.058. Epub 2022 Aug 4.

¹ Saïd Business School, Oxford University, Oxford, United Kingdom. Electronic address: agni.orfanoudaki@sbs.ox.ac.uk.
² Department of Cardiovascular Surgery, Mayo Clinic, Rochester, Minnesota.
³ Division of Cardiac Surgery, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
⁴ Department of Cardiovascular and Thoracic Surgery, West Virginia University, Morgantown, West Virginia.
⁵ Division of Cardiothoracic Surgery, Emory University School of Medicine Atlanta, Georgia.
⁶ The Society of Thoracic Surgeons, Chicago, Illinois.
⁷ Department of Cardiac Surgery, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California.
⁸ Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts.

No abstract available

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