ResearcherUniversity of VirginiaNo recent work listed
Armita Salahi
Matched on OpenAlex author ID A5067581431. Sources: OpenAlex.
Their work
- Papers
- 2 (first author 1, last author 0)
- Trials
- 0
- Grants
- 0
- Labs led
- 0
- Collaborators
- 3
2022: 1 paper · 2023: 1 paper
Papers 2
- Supervised learning on impedance cytometry data for label-free biophysical distinction of pancreatic cancer cells versus their associated fibroblasts under gem… Co-author DOI 10.1016/j.bios.2023.115262↗
- Automated biophysical classification of apoptotic pancreatic cancer cell subpopulations by using machine learning approaches with impedance cytometry. First author DOI 10.1039/d2lc00304j↗
Closest collaborators
The 3 strongest of 3 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.
- Nathan S. Swami · 2 shared papers, 2022–2023 · strength 0.40
- Paper Supervised learning on impedance cytometry data for label-free biophysical distinction of pancreatic cancer cells versu… DOI 10.1016/j.bios.2023.115262↗
- Paper Automated biophysical classification of apoptotic pancreatic cancer cell subpopulations by using machine learning appro… DOI 10.1039/d2lc00304j↗
- Carlos Honrado · 2 shared papers, 2022–2023 · strength 0.40
- Paper Supervised learning on impedance cytometry data for label-free biophysical distinction of pancreatic cancer cells versu… DOI 10.1016/j.bios.2023.115262↗
- Paper Automated biophysical classification of apoptotic pancreatic cancer cell subpopulations by using machine learning appro… DOI 10.1039/d2lc00304j↗
- Todd W. Bauer · 2 shared papers, 2022–2023 · strength 0.40
- Paper Supervised learning on impedance cytometry data for label-free biophysical distinction of pancreatic cancer cells versu… DOI 10.1016/j.bios.2023.115262↗
- Paper Automated biophysical classification of apoptotic pancreatic cancer cell subpopulations by using machine learning appro… DOI 10.1039/d2lc00304j↗
How to reach this person
A chain of introductions through people who have published, run trials or held grants together (warm_path@1: fewest links first, then the strongest). Built from public records only; no contact details are kept.