C4.5: programs for machine learning
C4.5: programs for machine learning
Proceedings of the 32nd conference on Winter simulation
Machine Learning
Logistic regression and artificial neural network classification models: a methodology review
Journal of Biomedical Informatics
Information Systems Research
Computational Statistics & Data Analysis
Decision support systems unfrastructure: The root problems of the management of changing IT
Decision Support Systems
Single and multiple time-point prediction models in kidney transplant outcomes
Journal of Biomedical Informatics
Exploring contributions of public resources in social bookmarking systems
Decision Support Systems
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
UWIS: An assessment methodology for usability of web-based information systems
Journal of Systems and Software
A machine learning-based approach to prognostic analysis of thoracic transplantations
Artificial Intelligence in Medicine
Advanced Data Mining Techniques
Advanced Data Mining Techniques
Diagnosing diabetes using neural networks on small mobile devices
Expert Systems with Applications: An International Journal
An analytic approach to better understanding and management of coronary surgeries
Decision Support Systems
Optimizing the facility location design of organ transplant centers
Decision Support Systems
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Lung transplantation has a vital role among all organ transplant procedures since it is the only accepted treatment for the end-stage pulmonary failure. There have been several research attempts to model the performance of lung transplants. Yet, these early studies either lack model predictive capability by relying on strong statistical assumptions or provide adequate predictive capability but suffer from less interpretability to the medical professionals. The proposed method described in this paper is focused on overcoming these limitations by providing a structural equation modeling-based decision tree construction procedure for lung transplant performance evaluation. Specifically, partial least squares-based path modeling algorithm is used for the structural equation modeling part. The proposed method is validated through a US nation-wide dataset obtained from United Network for Organ Sharing (UNOS). The results are promising in terms of both prediction and interpretation capabilities, and are superior to the existing techniques. Hence, we assert that a decision support system, which is based on the proposed method, can bridge the knowledge-gap between the large amount of available data and betterment of the lung transplantation procedures.