Cargando…
Label-Free Assessment of the Drug Resistance of Epithelial Ovarian Cancer Cells in a Microfluidic Holographic Flow Cytometer Boosted through Machine Learning
[Image: see text] About 75% of epithelial ovarian cancer (EOC) patients suffer from relapsing and develop drug resistance after primary chemotherapy. The commonly used clinical examinations and biological tumor tissue models for chemotherapeutic sensitivity are time-consuming and expensive. Research...
Autores principales: | Xin, Lu, Xiao, Wen, Che, Leiping, Liu, JinJin, Miccio, Lisa, Bianco, Vittorio, Memmolo, Pasquale, Ferraro, Pietro, Li, Xiaoping, Pan, Feng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2021
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8613806/ https://www.ncbi.nlm.nih.gov/pubmed/34841147 http://dx.doi.org/10.1021/acsomega.1c04204 |
Ejemplares similares
-
Developing a Reliable Holographic Flow Cyto-Tomography Apparatus by Optimizing the Experimental Layout and Computational Processing
por: Běhal, Jaromír, et al.
Publicado: (2022) -
AI-aided holographic flow cytometry for label-free identification of ovarian cancer cells in the presence of unbalanced datasets
por: Borrelli, F., et al.
Publicado: (2023) -
Phenotyping neuroblastoma cells through intelligent scrutiny of stain-free biomarkers in holographic flow cytometry
por: Pirone, Daniele, et al.
Publicado: (2023) -
Learning Diatoms Classification from a Dry Test Slide by Holographic Microscopy
por: Memmolo, Pasquale, et al.
Publicado: (2020) -
Beyond conventional microscopy: Observing kidney tissues by means of fourier ptychography
por: Valentino, Marika, et al.
Publicado: (2023)