Journal article

Machine-Learning Algorithms Predict Graft Failure After Liver Transplantation

Lawrence Lau, Yamuna Kankanige, Benjamin Rubinstein, Robert Jones, Christopher Christophi, Vijayaragavan Muralidharan, James Bailey

Transplantation | LIPPINCOTT WILLIAMS & WILKINS | Published : 2017

DOI: 10.1097/TP.0000000000001600

Grants

Funding Acknowledgements

The authors were supported in part by the Royal Australasian College of Surgeons Surgeon Scientist Research Scholarship, the Avant Doctor in Training Research Scholarship and the Australian Postgraduate Award.

Citation metrics

14Web of Science
16Scopus

Keywords

Area Under Curve
Artificial Neural-Networks
Algorithms
D-Meld
Machine Learning
Life Sciences & Biomedicine
Middle Aged
Victoria
Variable Importance Measure
Transplantation
Classification
Time Factors
Decision Support Techniques
Reproducibility of Results
Random Forests
Young Adult
Risk Factors
Surgery
Graft Survival
Female
Adolescent
Databases, Factual
Humans
Risk Assessment
Patient Selection
Donor Selection
Of-The-Art
Immunology
Patient Survival
Science & Technology
Predictive Value of Tests
Roc Curve
Donor Risk Index
Liver Transplantation
Male
Tissue Donors
Adult
Aged
Missing Data
Model
Treatment Failure