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Synthetic semi-supervised learning in imbalanced domains: Constructing a model for donor-recipient matching in liver transplantation

  • Published:2017-05 Issue: Volume:123 Page:75-87
  • ISSN:0950-7051
  • Container-title:Knowledge-Based Systems
  • language:en
  • Short-container-title:Knowledge-Based Systems

Author:

Pérez-Ortiz M.,Gutiérrez P.A.,Ayllón-Terán M.D.,Heaton N.,Ciria R.,Briceño J.,Hervás-Martínez C.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference37 articles.

1. The imbalanced training sample problem: under or over sampling?;Barandela,2004

2. Use of artificial intelligence as an innovative donor-recipient matching model for liver transplantation: results from a multicenter spanish study;Briceño;J. Hepatol.,2014

3. A proposal for scoring marginal liver grafts;Briceño;Transplant Int.,2000

4. The utility of marginal donors in liver transplantation;Busuttil;Liver Transplant,2003

5. Semi-supervised discriminant analysis;Cai,2007

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