Predicting Short-term Survival after Liver Transplantation using Machine Learning

Volume: 10, Issue: 1
Published: Mar 27, 2020
Abstract
Liver transplantation is one of the most effective treatments for end-stage liver disease, but the demand for livers is much higher than the available donor livers. Model for End-stage Liver Disease (MELD) score is a commonly used approach to prioritize patients, but previous studies have indicated that MELD score may fail to predict well for the postoperative patients. This work proposes to use data-driven approach to devise a predictive model...
Paper Details
Title
Predicting Short-term Survival after Liver Transplantation using Machine Learning
Published Date
Mar 27, 2020
Volume
10
Issue
1
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.