Predicting Post-Heart Transplant Composite Renal Outcome Risk in Adults: A Machine Learning Decision Tool

Affiliations

• ¹ Department of Computer Science, Texas A&M University-Commerce, Commerce, Texas, USA.
• ² Information Systems, Naveen Jindal School of Business, University of Texas at Dallas, Richardson, Texas, USA.
• ³ Division of Nephrology, University of Arizona College of Medicine-Tucson, Tucson, Arizona, USA.
• ⁴ Division of Cardiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
• ⁵ Division of Cardiovascular and Thoracic Surgery, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
• ⁶ Division of Nephrology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
• ⁷ Virginia Commonwealth University, Information Systems, School of Business, Richmond, Virginia, USA.
• ⁸ School of Public Health at the University of Texas Health Science Center, Dallas, Texas, USA.
• ⁹ Division of Nephrology, Banner University Medical Group-Tucson, Tucson, Arizona, USA.
• ¹⁰ School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Texas, USA.
• ¹¹ Dallas Nephrology Associates, Dallas, Texas, USA.
• ¹² Department of Surgery, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
• ¹³ Division of Nephrology, Medical University of South Carolina, Lancaster, South Carolina, USA.
• ¹⁴ Division of Nephrology, Virginia Commonwealth University, Richmond, Virginia, USA.