ResearcherJohns Hopkins UniversityNo recent work listed

Yan Wang

ORCID-verified (high confidence, 0.95), identity_conf@1As of 8 November 2026

Matched on ORCID iD 0000-0002-6728-8825; OpenAlex author ID A5100322762. Sources: OpenAlex.

Their work

Papers: 3 (first author 1, last author 0)
Trials: 0
Grants: 0
Labs led: 0
Collaborators: 13

Papers, trials and grants by year

2019: 2 papers · 2020: none · 2021: none · 2022: none · 2023: 1 paper

Papers 3

Exploration of Risk Factors for Pancreatic Cancer and Development of a Clinical High-Risk Group Rating Scale. First author DOI 10.3390/jcm12010358 ↗
Application of Deep Learning to Pancreatic Cancer Detection: Lessons Learned From Our Initial Experience. Co-author DOI 10.1016/j.jacr.2019.05.034 ↗
Pancreatic cancer biomarker detection by two support vector strategies for recursive feature elimination. Co-author DOI 10.2217/bmm-2018-0273 ↗

Closest collaborators

The 13 strongest of 13 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.

Qian Zhao · 1 shared paper, 2023 · strength 0.20
- Paper Exploration of Risk Factors for Pancreatic Cancer and Development of a Clinical High-Risk Group Rating Scale. DOI 10.3390/jcm12010358 ↗
Zhigang Wei · 1 shared paper, 2023 · strength 0.20
- Paper Exploration of Risk Factors for Pancreatic Cancer and Development of a Clinical High-Risk Group Rating Scale. DOI 10.3390/jcm12010358 ↗
Yongfei Tan · 1 shared paper, 2019 · strength 0.10
- Paper Pancreatic cancer biomarker detection by two support vector strategies for recursive feature elimination. DOI 10.2217/bmm-2018-0273 ↗
Hao Wang · 1 shared paper, 2019 · strength 0.10
- Paper Pancreatic cancer biomarker detection by two support vector strategies for recursive feature elimination. DOI 10.2217/bmm-2018-0273 ↗
Karen M Horton · 1 shared paper, 2019 · strength 0.07
- Paper Application of Deep Learning to Pancreatic Cancer Detection: Lessons Learned From Our Initial Experience. DOI 10.1016/j.jacr.2019.05.034 ↗
Bert Vogelstein · 1 shared paper, 2019 · strength 0.07
- Paper Application of Deep Learning to Pancreatic Cancer Detection: Lessons Learned From Our Initial Experience. DOI 10.1016/j.jacr.2019.05.034 ↗
Alan Yuille · 1 shared paper, 2019 · strength 0.07
- Paper Application of Deep Learning to Pancreatic Cancer Detection: Lessons Learned From Our Initial Experience. DOI 10.1016/j.jacr.2019.05.034 ↗
Seyoun Park · 1 shared paper, 2019 · strength 0.07
- Paper Application of Deep Learning to Pancreatic Cancer Detection: Lessons Learned From Our Initial Experience. DOI 10.1016/j.jacr.2019.05.034 ↗
Kenneth W. Kinzler · 1 shared paper, 2019 · strength 0.07
- Paper Application of Deep Learning to Pancreatic Cancer Detection: Lessons Learned From Our Initial Experience. DOI 10.1016/j.jacr.2019.05.034 ↗
Satomi Kawamoto · 1 shared paper, 2019 · strength 0.07
- Paper Application of Deep Learning to Pancreatic Cancer Detection: Lessons Learned From Our Initial Experience. DOI 10.1016/j.jacr.2019.05.034 ↗
Elliot K. Fishman · 1 shared paper, 2019 · strength 0.07
- Paper Application of Deep Learning to Pancreatic Cancer Detection: Lessons Learned From Our Initial Experience. DOI 10.1016/j.jacr.2019.05.034 ↗
Ralph H. Hruban MD · 1 shared paper, 2019 · strength 0.07
- Paper Application of Deep Learning to Pancreatic Cancer Detection: Lessons Learned From Our Initial Experience. DOI 10.1016/j.jacr.2019.05.034 ↗
Linda Chi Hang Chu · 1 shared paper, 2019 · strength 0.07
- Paper Application of Deep Learning to Pancreatic Cancer Detection: Lessons Learned From Our Initial Experience. DOI 10.1016/j.jacr.2019.05.034 ↗

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.