Automated biophysical classification of apoptotic pancreatic cancer cell subpopulations by using machine learning approaches with impedance cytometry
Abstract
Machine learning applied to impedance cytometry data enables biophysical recognition of cellular subpopulations over the apoptotic progression after gemcitabine treatment of pancreatic cancer cells from tumor xenografts.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 01, 2022
- Source ID
- 10.1039/d2lc00304j
Entities
People
- Armita Salahi
- Carlos Honrado
- John H Moore
- Nathan S. Swami
- Sara J Adair
- Todd W. Bauer
Organizations
- Air Force Office of Scientific Research
- National Cancer Institute
- National Center for Advancing Translational Sciences
- National Science Foundation
- University of Virginia