Recommendations for using artificial intelligence in clinical flow cytometry.
Saved in:
| Title: | Recommendations for using artificial intelligence in clinical flow cytometry. |
|---|---|
| Authors: | Ng DP; Department of Pathology, University of Utah, Salt Lake City, Utah, USA., Simonson PD; Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York, USA., Tarnok A; Department of Preclinical Development and Validation, Fraunhofer Institute for Cell Therapy and Immunology, IZI, Leipzig, Germany., Lucas F; Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA., Kern W; MLL Munich Leukemia Laboratory GmbH, Munich, Germany., Rolf N; BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada., Bogdanoski G; Clinical Development & Operations Quality, R&D Quality, Bristol Myers Squibb, Princeton, New Jersey, USA., Green C; Translational Science, Ozette Technologies, Seattle, Washington, USA., Brinkman RR; Dotmatics, Inc, Boston, Massachusetts, USA., Czechowska K; Metafora Biosystems, PARIS, France. |
| Source: | Cytometry. Part B, Clinical cytometry [Cytometry B Clin Cytom] 2024 Jul; Vol. 106 (4), pp. 228-238. Date of Electronic Publication: 2024 Feb 26. |
| Publication Type: | Journal Article; Review |
| Journal Info: | Publisher: Wiley-Liss Country of Publication: United States NLM ID: 101235690 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1552-4957 (Electronic) Linking ISSN: 15524949 NLM ISO Abbreviation: Cytometry B Clin Cytom Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
| ISSN: | 1552-4957 |
|---|---|
| DOI: | 10.1002/cyto.b.22166 |
