Jeongin Yoo

Closest collaborators

The 14 strongest of 14 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.

1. Jeong Hee Yoon · 2 shared papers, 2023–2026 · strength 0.51
   • Paper Deep learning-based combined noise reduction and contrast enhancement for post-neoadjuvant pancreatic cancer CT: does i… DOI 10.1007/s00261-025-05271-6↗
   • Paper Post-neoadjuvant treatment pancreatic cancer resectability and outcome prediction using CT, 18F-FDG PET/MRI and CA 19-9. DOI 10.1186/s40644-023-00565-8↗
2. Jeong Min Lee · 2 shared papers, 2023–2026 · strength 0.51
   • Paper Deep learning-based combined noise reduction and contrast enhancement for post-neoadjuvant pancreatic cancer CT: does i… DOI 10.1007/s00261-025-05271-6↗
   • Paper Post-neoadjuvant treatment pancreatic cancer resectability and outcome prediction using CT, 18F-FDG PET/MRI and CA 19-9. DOI 10.1186/s40644-023-00565-8↗
3. Jin‐Young Jang · 2 shared papers, 2023 · strength 0.46
   • Paper Body composition analysis using convolutional neural network in predicting postoperative pancreatic fistula and surviva… DOI 10.1016/j.ejrad.2023.111182↗
   • Paper Post-neoadjuvant treatment pancreatic cancer resectability and outcome prediction using CT, 18F-FDG PET/MRI and CA 19-9. DOI 10.1186/s40644-023-00565-8↗
4. Sae‐Jin Park · 1 shared paper, 2026 · strength 0.39
   • Paper Prediction of tumor regression grade and identification of prognostic factors using CT and biological features in patie… DOI 10.1177/02841851261424497↗
5. Haeryoung Kim · 1 shared paper, 2026 · strength 0.39
   • Paper Prediction of tumor regression grade and identification of prognostic factors using CT and biological features in patie… DOI 10.1177/02841851261424497↗
6. Jung Hoon Kim · 1 shared paper, 2026 · strength 0.39
   • Paper Prediction of tumor regression grade and identification of prognostic factors using CT and biological features in patie… DOI 10.1177/02841851261424497↗
7. Seok Jin Hong · 1 shared paper, 2026 · strength 0.32
   • Paper Deep learning-based combined noise reduction and contrast enhancement for post-neoadjuvant pancreatic cancer CT: does i… DOI 10.1007/s00261-025-05271-6↗
8. Hyo‐Jin Kang · 1 shared paper, 2026 · strength 0.32
   • Paper Deep learning-based combined noise reduction and contrast enhancement for post-neoadjuvant pancreatic cancer CT: does i… DOI 10.1007/s00261-025-05271-6↗
9. Sun Kyung Jeon · 1 shared paper, 2026 · strength 0.32
   • Paper Deep learning-based combined noise reduction and contrast enhancement for post-neoadjuvant pancreatic cancer CT: does i… DOI 10.1007/s00261-025-05271-6↗
10. Liang Zhu · 1 shared paper, 2026 · strength 0.32
    • Paper Deep learning-based combined noise reduction and contrast enhancement for post-neoadjuvant pancreatic cancer CT: does i… DOI 10.1007/s00261-025-05271-6↗
11. Dong Ho Lee · 1 shared paper, 2023 · strength 0.26
    • Paper Body composition analysis using convolutional neural network in predicting postoperative pancreatic fistula and surviva… DOI 10.1016/j.ejrad.2023.111182↗
12. Ijin Joo · 1 shared paper, 2023 · strength 0.19
    • Paper Post-neoadjuvant treatment pancreatic cancer resectability and outcome prediction using CT, 18F-FDG PET/MRI and CA 19-9. DOI 10.1186/s40644-023-00565-8↗
13. Mi Hye Yu · 1 shared paper, 2023 · strength 0.19
    • Paper Post-neoadjuvant treatment pancreatic cancer resectability and outcome prediction using CT, 18F-FDG PET/MRI and CA 19-9. DOI 10.1186/s40644-023-00565-8↗
14. Sang Hyub Lee · 1 shared paper, 2023 · strength 0.19
    • Paper Post-neoadjuvant treatment pancreatic cancer resectability and outcome prediction using CT, 18F-FDG PET/MRI and CA 19-9. DOI 10.1186/s40644-023-00565-8↗

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.