Personalized prediction of esophageal cancer risk based on virtually generated alcohol data
Overall, our findings highlight the importance of integrating virtually generated alcohol data for more precise personalized risk assessments for EC.
Authors
- Mong‐Wei Lin (ORCID: https://orcid.org/0000-0003-1268-3729)
- Oswald Ndi Nfor
- Ke-Cheng Chen
- Yung‐Po Liaw (ORCID: https://orcid.org/0000-0003-2046-4964)
- Shuenn‐Wen Kuo (ORCID: https://orcid.org/0000-0001-5026-5582)
- Jang‐Ming Lee (ORCID: https://orcid.org/0000-0001-9727-227X)
- Ming‐Fang Wu (ORCID: https://orcid.org/0000-0002-7208-7067)
- Yu‐Kwang Lee
- Pei‐Ming Huang (ORCID: https://orcid.org/0000-0001-5493-7673)
- Ying‐Hsiang Chou (ORCID: https://orcid.org/0000-0001-5888-4302)
- Chih‐Hung Hsu (ORCID: https://orcid.org/0000-0003-0495-973X)
- Ji-Han Zhong
Institutions
- National Taiwan University (TW)
- Chung Shan Medical University Hospital (TW)
- National Taiwan University Hospital (TW)
- Chung Shan Medical University (TW)
Publication Details
- Journal
- Journal of Translational Medicine
- Published
- 2025-03-28
- DOI
- https://doi.org/10.1186/s12967-025-06383-9
- Citations
- 1
- Primary Topic
- Esophageal Cancer Research and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 2.01
Funders
- Ministry of Science and Technology, Taiwan
- Health Promotion Administration, Ministry of Health and Welfare