Morphological Signal Processing for Phenotype Recognition of Human Pluripotent Stem Cells Using Machine Learning Methods
- DOI
- 10.3390/biomedicines11113005
- Published
- 2023-11-09
- Container
- Biomedicines
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/biomedicines11113005,
title = {Morphological Signal Processing for Phenotype Recognition of Human Pluripotent Stem Cells Using Machine Learning Methods},
author = {Ekaterina Vedeneeva and Vitaly Gursky and Maria Samsonova and Irina Neganova},
year = {2023},
journal = {Biomedicines},
doi = {10.3390/biomedicines11113005},
url = {https://doi.org/10.3390/biomedicines11113005}
}RIS
TY - JOUR TI - Morphological Signal Processing for Phenotype Recognition of Human Pluripotent Stem Cells Using Machine Learning Methods AU - Ekaterina Vedeneeva AU - Vitaly Gursky AU - Maria Samsonova AU - Irina Neganova PY - 2023 JO - Biomedicines DO - 10.3390/biomedicines11113005 UR - https://doi.org/10.3390/biomedicines11113005 ER -
APA
Vedeneeva, E., Gursky, V., Samsonova, M., & Neganova, I. (2023). Morphological Signal Processing for Phenotype Recognition of Human Pluripotent Stem Cells Using Machine Learning Methods. Biomedicines. https://doi.org/10.3390/biomedicines11113005
Source records
- crossref · retrieved 2026-09-26T18:25:06.231Z