ResearcherMayo ClinicActive in the last 2 years

Shivaram P. Arunachalam

ORCID-verified (high confidence, 0.95), identity_conf@1As of 7 November 2026

Matched on ORCID iD 0000-0003-3251-5415; OpenAlex author ID A5002606430. Sources: OpenAlex.

Their work

Papers: 2 (first author 0, last author 1)
Trials: 0
Grants: 0
Labs led: 0
Collaborators: 5

Papers, trials and grants by year

2023: 1 paper · 2024: 1 paper

Papers 2

Machine Learning Models for Pancreatic Cancer Risk Prediction Using Electronic Health Record Data-A Systematic Review and Assessment. Co-author DOI 10.14309/ajg.0000000000002870 ↗
Prospective of Pancreatic Cancer Diagnosis Using Cardiac Sensing. Last author DOI 10.3390/jimaging9080149 ↗

Closest collaborators

The 5 strongest of 5 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.

Anup Kumar Mishra · 1 shared paper, 2024 · strength 0.28
- Paper Machine Learning Models for Pancreatic Cancer Risk Prediction Using Electronic Health Record Data-A Systematic Review a… DOI 10.14309/ajg.0000000000002870 ↗
Bradford Chong · 1 shared paper, 2024 · strength 0.28
- Paper Machine Learning Models for Pancreatic Cancer Risk Prediction Using Electronic Health Record Data-A Systematic Review a… DOI 10.14309/ajg.0000000000002870 ↗
Ann L. Oberg · 1 shared paper, 2024 · strength 0.28
- Paper Machine Learning Models for Pancreatic Cancer Risk Prediction Using Electronic Health Record Data-A Systematic Review a… DOI 10.14309/ajg.0000000000002870 ↗
Shounak Majumder · 1 shared paper, 2024 · strength 0.28
- Paper Machine Learning Models for Pancreatic Cancer Risk Prediction Using Electronic Health Record Data-A Systematic Review a… DOI 10.14309/ajg.0000000000002870 ↗
Mansunderbir Singh · 1 shared paper, 2023 · strength 0.18
- Paper Prospective of Pancreatic Cancer Diagnosis Using Cardiac Sensing. DOI 10.3390/jimaging9080149 ↗

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.