ResearcherHarvard UniversityNo recent work listed
Kyu Ha Lee
Matched on ORCID iD 0000-0002-5313-8375; OpenAlex author ID A5103252191. Sources: OpenAlex.
Their work
- Papers
- 2
- Trials
- 0
- Grants
- 0
- Labs led
- 0
- Collaborators
- 3
2015: 1 paper · 2016: 1 paper
Papers 2
- Hierarchical models for semi-competing risks data with application to quality of end-of-life care for pancreatic cancer. Co-author DOI 10.1080/01621459.2016.1164052↗
- Bayesian Semi-parametric Analysis of Semi-competing Risks Data: Investigating Hospital Readmission after a Pancreatic Cancer Diagnosis. Co-author DOI 10.1111/rssc.12078↗
Closest collaborators
The 3 strongest of 3 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.
- Deborah Schrag · 2 shared papers, 2015–2016 · strength 0.16
- Paper Hierarchical models for semi-competing risks data with application to quality of end-of-life care for pancreatic cancer. DOI 10.1080/01621459.2016.1164052↗
- Paper Bayesian Semi-parametric Analysis of Semi-competing Risks Data: Investigating Hospital Readmission after a Pancreatic C… DOI 10.1111/rssc.12078↗
- Francesca Dominici · 2 shared papers, 2015–2016 · strength 0.16
- Paper Hierarchical models for semi-competing risks data with application to quality of end-of-life care for pancreatic cancer. DOI 10.1080/01621459.2016.1164052↗
- Paper Bayesian Semi-parametric Analysis of Semi-competing Risks Data: Investigating Hospital Readmission after a Pancreatic C… DOI 10.1111/rssc.12078↗
- Sebastien Haneuse · 2 shared papers, 2015–2016 · strength 0.16
- Paper Hierarchical models for semi-competing risks data with application to quality of end-of-life care for pancreatic cancer. DOI 10.1080/01621459.2016.1164052↗
- Paper Bayesian Semi-parametric Analysis of Semi-competing Risks Data: Investigating Hospital Readmission after a Pancreatic C… DOI 10.1111/rssc.12078↗
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.