Machine learning potential predictor of idiopathic pulmonary fibrosis
This study highlights their potential for early biomarker discovery and risk prediction in IPF, offering insights into disease mechanisms and diagnostic strategies.
Authors
- Junjie He (ORCID: https://orcid.org/0000-0001-7164-8216)
- Renjie Zuo
- Sunkui Ke
- Quan Liao (ORCID: https://orcid.org/0000-0003-1324-6213)
- Weibin Chen (ORCID: https://orcid.org/0000-0001-5096-4551)
- Shichao Zhang (ORCID: https://orcid.org/0000-0001-9981-2970)
- Zhenzhen Guo (ORCID: https://orcid.org/0009-0003-1364-6628)
- Ziwei Ye
- Chenchun Ding (ORCID: https://orcid.org/0009-0008-0803-1369)
Institutions
- Xiamen University (CN)
- Zhongshan Hospital of Xiamen University (CN)
- Second Hospital of Tianjin Medical University (CN)
- Tianjin Medical University (CN)
Publication Details
- Journal
- Frontiers in Genetics
- Published
- 2025-01-22
- DOI
- https://doi.org/10.3389/fgene.2024.1464471
- Primary Topic
- Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
- Type
- article
- Field-Weighted Citation Impact
- 0.00