This paper is in the following e-collection/theme issue:

Machine Learning (1401) Clinical Information and Decision Making (1340) Decision Support for Health Professionals (1147)

Published on in Vol 10, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32313, first published .
Predicting Long-term Survival After Allogeneic Hematopoietic Cell Transplantation in Patients With Hematologic Malignancies: Machine Learning–Based Model Development and Validation

Predicting Long-term Survival After Allogeneic Hematopoietic Cell Transplantation in Patients With Hematologic Malignancies: Machine Learning–Based Model Development and Validation

Predicting Long-term Survival After Allogeneic Hematopoietic Cell Transplantation in Patients With Hematologic Malignancies: Machine Learning–Based Model Development and Validation

Authors of this article:

Eun-Ji Choi1 Author Orcid Image ;   Tae Joon Jun2 Author Orcid Image ;   Han-Seung Park1 Author Orcid Image ;   Jung-Hee Lee1 Author Orcid Image ;   Kyoo-Hyung Lee1 Author Orcid Image ;   Young-Hak Kim3 Author Orcid Image ;   Young-Shin Lee1 Author Orcid Image ;   Young-Ah Kang1 Author Orcid Image ;   Mijin Jeon1 Author Orcid Image ;   Hyeran Kang1 Author Orcid Image ;   Jimin Woo1 Author Orcid Image ;   Je-Hwan Lee1 Author Orcid Image
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Journals

  1. Afanaseva K, Bakin E, Smirnova A, Barkhatov I, Gindina T, Moiseev I, Bondarenko S. A pilot study of implication of machine learning for relapse prediction after allogeneic stem cell transplantation in adults with Ph-positive acute lymphoblastic leukemia. Scientific Reports 2023;13(1) View

Books/Policy Documents

  1. Hanselia R, Choubey D. International Conference on Innovative Computing and Communications. View