Predicting the Survival Status of Patient after Bone Marrow Transplant Using Fuzzy Discernibility Matrix
Author:
Affiliation:
1. KIIT Deemed to be University,School of Computer Engineering,Bhubaneshwar,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10113898/10113899/10114043.pdf?arnumber=10114043
Reference19 articles.
1. Machine Learning Approach for Identifying Survival of Bone Marrow Transplant Patients
2. Survival Prediction of Children Undergoing Hematopoietic Stem Cell Transplantation Using Different Machine Learning Classifiers by Performing Chi-squared Test and Hyperparameter Optimization: A Retrospective Analysis;ratul;arXiv preprint arXiv 2201 08987,2022
3. Machine Learning Methods to Better Predict Post-Hematopoietic Stem Cell Transplant (HSCT) Leukemic Relapse in Pediatric Patients with Acute Lymphoblastic Leukemia: Random Forest (RF) Classification Featuring Serial Post-Transplant Lineage-Specific Chimerism;shyr;Blood 136,2020
4. Treatment outcome classification of pediatric Acute Lymphoblastic Leukemia patients with clinical and medical data using machine learning: A case study at MAHAK hospital
5. Machine learning applications for prediction of relapse in childhood acute lymphoblastic leukemia
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