Automated Flow Cytometric MRD Assessment in Childhood Acute B‐ Lymphoblastic Leukemia Using Supervised Machine Learning-Reference-Cited by-同舟云学术

Automated Flow Cytometric MRD Assessment in Childhood Acute B‐ Lymphoblastic Leukemia Using Supervised Machine Learning

Published:2019-07-07 Issue:9 Volume:95 Page:966-975
ISSN:1552-4922
Container-title:Cytometry Part A
language:en
Short-container-title:Cytometry

Author:

Reiter Michael¹²,Diem Markus¹²,Schumich Angela¹,Maurer‐Granofszky Margarita¹,Karawajew Leonid³,Rossi Jorge G.⁴,Ratei Richard⁵,Groeneveld‐Krentz Stefanie³,Sajaroff Elisa O.⁴,Suhendra Susanne⁶,Kampel Martin²,Dworzak Michael N.¹⁶,

Affiliation:

1. Immunological Diagnostics, Children's Cancer Research Institute Vienna Austria

2. Computer Vision Lab, Faculty of InformaticsTechnical University of Vienna Vienna Austria

3. Department of Pediatric Oncology/HematologyCharité Universitätsmedizin Berlin Berlin Germany

4. Cellular Immunology LaboratoryHospital de Pediatria “Dr. Juan P. Garrahan” Buenos Aires Argentina

5. Department of Hematology, Oncology and Tumor ImmunologyHELIOS Klinikum Berlin‐Buch Berlin Germany

6. Labdia Labordiagnostik GmbH Vienna Austria

Funder

Deutsche Kinderkrebsstiftung

Publisher

Wiley

Subject

Cell Biology,Histology,Pathology and Forensic Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cyto.a.23852

Reference40 articles.

1. Acute lymphoblastic leukaemia

2. Treatment of Childhood Acute Lymphoblastic Leukemia

3. Use of Allogeneic Hematopoietic Stem-Cell Transplantation Based on Minimal Residual Disease Response Improves Outcomes for Children With Relapsed Acute Lymphoblastic Leukemia in the Intermediate-Risk Group

4. Risk of Relapse of Childhood Acute Lymphoblastic Leukemia Is Predicted By Flow Cytometric Measurement of Residual Disease on Day 15 Bone Marrow

5. Clinical significance of minimal residual disease in childhood acute lymphoblastic leukemia and its relationship to other prognostic factors: a Children's Oncology Group study

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