Predicting ideal outcome after pediatric liver transplantation: An exploratory study using machine learning analyses to leverage Studies of Pediatric Liver Transplantation Data.
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| Title: | Predicting ideal outcome after pediatric liver transplantation: An exploratory study using machine learning analyses to leverage Studies of Pediatric Liver Transplantation Data. |
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| Authors: | Wadhwani SI; Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio., Hsu EK; University of Washington School of Medicine, Seattle Children's Hospital, Seattle, Washington., Shaffer ML; University of Washington, Seattle, Washington., Anand R; EMMES Corporation, Rockville, Maryland., Ng VL; Transplant and Regenerative Medicine Center, Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada., Bucuvalas JC; Icahn School of Medicine at Mount Sinai, Kravis Children's Hospital, New York, New York. |
| Source: | Pediatric transplantation [Pediatr Transplant] 2019 Nov; Vol. 23 (7), pp. e13554. Date of Electronic Publication: 2019 Jul 22. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Munksgaard Country of Publication: Denmark NLM ID: 9802574 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1399-3046 (Electronic) Linking ISSN: 13973142 NLM ISO Abbreviation: Pediatr Transplant Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1399-3046 |
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| DOI: | 10.1111/petr.13554 |
