ResearcherMedical College of WisconsinNo recent work listed
Haidy Gerges Nasief
Matched on ORCID iD 0000-0002-5591-5094; OpenAlex author ID A5064062214. Sources: OpenAlex.
Their work
- Papers
- 2
- Trials
- 0
- Grants
- 0
- Labs led
- 0
- Collaborators
- 5
2019: 2 papers
Papers 2
- A machine learning based delta-radiomics process for early prediction of treatment response of pancreatic cancer. Co-author DOI 10.1038/s41698-019-0096-z↗
- Improving Treatment Response Prediction for Chemoradiation Therapy of Pancreatic Cancer Using a Combination of Delta-Radiomics and the Clinical Biomarker CA19-… Co-author DOI 10.3389/fonc.2019.01464↗
Closest collaborators
The 5 strongest of 5 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.
- William Adrian Hall · 2 shared papers, 2019 · strength 0.21
- Paper A machine learning based delta-radiomics process for early prediction of treatment response of pancreatic cancer. DOI 10.1038/s41698-019-0096-z↗
- Paper Improving Treatment Response Prediction for Chemoradiation Therapy of Pancreatic Cancer Using a Combination of Delta-Ra… DOI 10.3389/fonc.2019.01464↗
- X. Allen Li · 2 shared papers, 2019 · strength 0.21
- Paper A machine learning based delta-radiomics process for early prediction of treatment response of pancreatic cancer. DOI 10.1038/s41698-019-0096-z↗
- Paper Improving Treatment Response Prediction for Chemoradiation Therapy of Pancreatic Cancer Using a Combination of Delta-Ra… DOI 10.3389/fonc.2019.01464↗
- Beth E. Erickson · 2 shared papers, 2019 · strength 0.21
- Paper A machine learning based delta-radiomics process for early prediction of treatment response of pancreatic cancer. DOI 10.1038/s41698-019-0096-z↗
- Paper Improving Treatment Response Prediction for Chemoradiation Therapy of Pancreatic Cancer Using a Combination of Delta-Ra… DOI 10.3389/fonc.2019.01464↗
- Liang Wang · 1 shared paper, 2019 · strength 0.11
- Susan Tsai · 1 shared paper, 2019 · strength 0.11
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.