Rapid diagnosis of hereditary haemolytic anaemias using automated rheoscopy and supervised machine learning
Publication date
2020-08
Authors
Moura, Pedro L
Dobbe, Johannes G G
Streekstra, Geert J
Rab, Minke A.E.
Veldthuis, Martijn
Fermo, Elisa
Van Wijk, Richard
van Zwieten, Rob
Bianchi, Paola
Toye, Ashley M
Editors
Advisors
Supervisors
Document Type
Letter
Metadata
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License
cc_by_nc
Abstract
Keywords
Anemia, Hemolytic, Congenital Nonspherocytic/blood, Anemia, Hemolytic, Congenital/blood, Automation, Blood Viscosity, Datasets as Topic, Erythrocyte Deformability, Erythrocytes, Abnormal/ultrastructure, Humans, Hydrops Fetalis/blood, Image Processing, Computer-Assisted/instrumentation, Pyruvate Kinase/blood, Pyruvate Metabolism, Inborn Errors/blood, Reticulocytes/ultrastructure, Single-Cell Analysis/instrumentation, Supervised Machine Learning, Letter, Research Support, Non-U.S. Gov't
Citation
Moura, P L, Dobbe, J G G, Streekstra, G J, Rab, M A E, Veldthuis, M, Fermo, E, van Wijk, R, van Zwieten, R, Bianchi, P, Toye, A M & Satchwell, T J 2020, 'Rapid diagnosis of hereditary haemolytic anaemias using automated rheoscopy and supervised machine learning', British Journal of Haematology, vol. 190, no. 4, pp. e250-e255. https://doi.org/10.1111/bjh.16868