Survival Prediction of Children Undergoing Hematopoietic Stem Cell Transplantation Using Different Machine Learning Classifiers by Performing Chi-Square Test and Hyperparameter Optimization: A Retrospective Analysis

Table 6

Performance comparison of our methodology with state-of-the-art ones.

References	Authors	Method	Findings
[55]	K. Karami et al.	ML with feature selection	Accuracy of 85.17% and AUC of 0.930
[56]	V. Leclerc et al.	Tree-augmented naïve Bayesian network	AUC-ROC of 0.804, 32.8% of misclassified patients
[58]	V. Hazar et al.	Kaplan–Meier method and test	Overall survival (OS) of 65% and event-free survival (EFS) rate of 48%
[59]	Y. T. Jiaqian Qi et al.	The Cox proportional hazard model and fine-gray competing risk model	Overall mortality (), nonrelapse mortality (), and combined endpoints ()
Proposed study		ML with Chi-squared test	Survival prediction accuracy of 94.73%