Machine learning predicts stem cell transplant response in severe scleroderma.

Abstract

Authors

• Jennifer M Franks
  Department of Molecular and Systems Biology.
• Viktor Martyanov
  Geisel School of Medicine at Dartmouth, Hanover, New Hampshire.
• Yue Wang
  Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
• Tammara A Wood
  Geisel School of Medicine at Dartmouth, Hanover, New Hampshire.
• Ashley Pinckney
  Rho Federal Systems Division, Chapel Hill, North Carolina, USA.
• Leslie J Crofford
  Department of Medicine, Vanderbilt University Medical Center, 1161 21st Avenue South T3113 MCN, Nashville, TN, 37232, USA.
• Lynette Keyes-Elstein
  Rho Federal Systems Division, Chapel Hill, North Carolina, USA.
• Daniel E Furst
  Department of Medicine, Division of Rheumatology, University of California at Los Angeles, Los Angeles, California, USA.
• Ellen Goldmuntz
  NIAID/NIH, Bethesda, Maryland, USA.
• Maureen D Mayes
  Rheumatology and Clinical Immunogenetics, The University of Texas Health Science Center Houston Medical School, Houston, Texas, USA.
• Peter McSweeney
  Rocky Mountain Blood and Marrow Transplant Program, Colorado Blood Cancer Institute, Denver, Colorado, USA.
• Richard A Nash
  Rocky Mountain Blood and Marrow Transplant Program, Colorado Blood Cancer Institute, Denver, Colorado, USA.
• Keith M Sullivan
  Duke University Medical Center, Durham, North Carolina, United States.
• Michael L Whitfield
  Department of Molecular and Systems Biology.

Keywords

External Resources