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] |
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| 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 | ||||
