Experiment Overview

Repository ID: FR-FCM-ZYVT Experiment name: Automated flow cytometric MRD Assessment in Childhood Acute B- Lymphoblastic Leukemia using Supervised Machine Learning MIFlowCyt score: 38.00%
Primary researcher: Margarita Maurer-Granofszky PI/manager: Michael Dworzak Uploaded by: Margarita Maurer-Granofszky
Experiment dates: 2006-01-01 - 2017-12-31 Dataset uploaded: Mar 2019 Last updated: Jul 2019
Keywords: [automated gating] [minimal residual disease] [machine learning] [B-ALL] [multiparameter flow cytometry] [acute lymphoblastic leukemia] [gaussian mixture model] [algorithm] Manuscripts: [31282025] Cytalogo
Organizations: None
Purpose: The purpose of this study was to develop an automated approach for FCM-MRD quantification in bone marrow samples of pediatric patients with B-acute lymphoblastic leukemia.
Conclusion: In conclusion, our proposed automated approach could potentially be used to assess FCM-MRD in B-ALL in an objective and standardized manner across different laboratories.
Comments: None
Funding: The study has been funded by the Marie Curie Industry Academia Partnership & Pathways (FP7-MarieCurie-PEOPLE-2013-IAPP) under grant no. 610872 to project “AutoFLOW” to MK, LK and MND, as well as by the Deutsche Kinderkrebsstiftung through project DKS2013.12 to LK.
Quality control: None
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