Predicting heart transplantation outcomes through data analytics

详细信息    查看全文

• 作者：Ali Dag^a ; ^{ali.dag@usd.edu}Author Vitae ; Asil Oztekin^b ; ^{Asil_Oztekin@uml.edu}Author Vitae ; Ahmet Yucel^c ; ^{azy0002@auburn.edu}Author Vitae ; Serkan Bulur^d ; ^{serkanbulur@gmail.com}Author Vitae ; Fadel M. Megahed^e ; ^{fmegahed@miamioh.edu}Author Vitae
• 关键词：Data mining ; Health-care analytics ; Medical decision making ; Transplants ; Unbalanced data ; United Network for Organ Sharing (UNOS)
• 刊名：Decision Support Systems
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：94
• 期：Complete
• 页码：42-52
• 全文大小：990 K
• 卷排序：94

文摘

A data-driven approach for predicting survival outcomes at multiple time-points is developed. The method successfully predicted short-, mid-, & long-term heart transplantation outcomes. The proposed method is unique in that it fills an important gap in the published literature. The approach is generic so it can be applied to other organ transplantation cases.