Review of flow cytometry findings and associated scoring approaches for identifying myelodysplastic syndrome and the future role of machine learning in improving the diagnostic algorithm.
Saved in:
| Title: | Review of flow cytometry findings and associated scoring approaches for identifying myelodysplastic syndrome and the future role of machine learning in improving the diagnostic algorithm. |
|---|---|
| Authors: | Demko N; Department of Anatomical Pathology, McGill University Health Center, Montréal, Québec, Canada.; Department of Pathology and Laboratory Medicine, Weill Cornell Medical College, New York, NY, United States., Geyer JT; Department of Pathology and Laboratory Medicine, Weill Cornell Medical College, New York, NY, United States., Simonson PD; Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States. |
| Source: | American journal of clinical pathology [Am J Clin Pathol] 2026 Jan 22; Vol. 165 (1). |
| Publication Type: | Journal Article; Review |
| Journal Info: | Publisher: Oxford University Press Country of Publication: England NLM ID: 0370470 Publication Model: Print Cited Medium: Internet ISSN: 1943-7722 (Electronic) Linking ISSN: 00029173 NLM ISO Abbreviation: Am J Clin Pathol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 1943-7722 |
|---|---|
| DOI: | 10.1093/ajcp/aqaf136 |