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Clustering of cell populations in flow cytometry data using a combination of Gaussian mixtures.

, , , , , and . Pattern Recognit., (2016)

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A Clinical Tool for Automated Flow Cytometry Based on Machine Learning Methods., , , , , , , , and . IWBBIO (2), volume 10209 of Lecture Notes in Computer Science, page 537-548. (2017)Towards Self-explainable Transformers for Cell Classification in Flow Cytometry Data., , , , , , , , , and 2 other author(s). iMIMIC@MICCAI, volume 13611 of Lecture Notes in Computer Science, page 22-32. Springer, (2022)WGAN Latent Space Embeddings for Blast Identification in Childhood Acute Myeloid Leukaemia., , , , , , , and . ICPR, page 3868-3873. IEEE Computer Society, (2018)Automated Immunophenotyping Assessment for Diagnosing Childhood Acute Leukemia using Set-Transformers., , , , and . CoRR, (2024)Clustering of cell populations in flow cytometry data using a combination of Gaussian mixtures., , , , , and . Pattern Recognit., (2016)Application of Machine Learning for Automatic MRD Assessment in Paediatric Acute Myeloid Leukaemia., , , , , and . ICPRAM, page 401-408. SciTePress, (2018)FATE: Feature-Agnostic Transformer-based Encoder for learning generalized embedding spaces in flow cytometry data., , , , , and . WACV, page 7941-7949. IEEE, (2024)