Patient‐based prediction algorithm of relapse after allo‐HSCT for acute Leukemia and its usefulness in the decision‐making process using a machine learning approach

Patient‐based prediction algorithm of relapse after allo‐HSCT for acute Leukemia and its usefulness in the decision‐making process using a machine learning approach

Abstract Although allogeneic hematopoietic stem cell transplantation (allo‐HSCT) is a curative therapy for high‐risk acute leukemia (AL), some patients still relapse. Since patients simultaneously have many prognostic factors, difficulties are associated with the construction of a patient‐based pred...

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Bibliographic Details
Main Authors: Kyoko Fuse, Shun Uemura, Suguru Tamura, Tatsuya Suwabe, Takayuki Katagiri, Tomoyuki Tanaka, Takashi Ushiki, Yasuhiko Shibasaki, Naoko Sato, Toshio Yano, Takashi Kuroha, Shigeo Hashimoto, Tatsuo Furukawa, Miwako Narita, Hirohito Sone, Masayoshi Masuko
Format: Article
Language:English
Published: Wiley 2019-09-01
Series:Cancer Medicine
Subjects:
acute leukemia
allogeneic hematopoietic stem cell transplantation
machine learning
patient‐based prediction
relapse posttransplantation
Online Access:https://doi.org/10.1002/cam4.2401

Internet

https://doi.org/10.1002/cam4.2401

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