Haematology dimension reduction, a large scale application to regular care haematology data
We conclude that for hematology data, the use of unsupervised dimension reduction techniques should be limited to data visualization applications, as implementing them in diagnostic pipelines may lead to decreased quality of integrated diagnostics in routine care.
Authors
- Saskia Haitjema (ORCID: https://orcid.org/0000-0001-5465-4868)
- Albert Huisman (ORCID: https://orcid.org/0000-0002-2291-2487)
- Wouter W. van Solinge (ORCID: https://orcid.org/0000-0003-2867-2581)
- Imo E. Hoefer (ORCID: https://orcid.org/0000-0002-8379-7814)
- Huibert-Jan Joosse (ORCID: https://orcid.org/0000-0002-2898-6954)
- Chontira Chumsaeng-Reijers
- Bram van Es (ORCID: https://orcid.org/0000-0003-4667-1304)
Institutions
- Utrecht University (NL)
- Heidelberg University (DE)
- University Hospital Heidelberg (DE)
- University Medical Center Utrecht (NL)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2025-02-12
- DOI
- https://doi.org/10.1186/s12911-025-02899-8
- Citations
- 2
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 1.61