A machine learning model for prediction of 30-day primary graft failure after heart transplantation

A machine learning model for prediction of 30-day primary graft failure after heart transplantation

Background: Primary graft failure (PGF) remains the most common cause of short-term mortality after heart transplantation. The main objective was to develop and validate a risk model for prediction of short-term mortality due to PGF after heart transplantation using the ISHLT Heart Transplant Regist...

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Bibliographic Details
Main Authors: Björn Linse, Mattias Ohlsson, Joseph Stehlik, Lars H. Lund, Bodil Andersson, Johan Nilsson
Format: Article
Language:English
Published: Elsevier 2023-03-01
Series:Heliyon
Subjects:
Heart transplantation
Primary graft failure
Artificial neural network
Prediction
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844023014895

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http://www.sciencedirect.com/science/article/pii/S2405844023014895

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