Machine learning-based integration develops an immune-derived signature for diagnosing high-altitude pulmonary hypertension
Our findings propose the minimally invasive blood-derived immune signature for HAPH diagnosis, providing a practical framework for early detection in resource-constrained high-altitude populations.
Authors
- Yanhui Qin (ORCID: https://orcid.org/0000-0002-6765-1508)
- Junqiang Gou (ORCID: https://orcid.org/0009-0007-1357-1469)
- Sizhe Wang (ORCID: https://orcid.org/0000-0001-6447-2435)
- Junjie Ma (ORCID: https://orcid.org/0000-0003-0429-0888)
- Jialin Wu (ORCID: https://orcid.org/0000-0003-2272-2541)
- Li Wu (ORCID: https://orcid.org/0000-0003-3596-2077)
- Yixuan Huang (ORCID: https://orcid.org/0000-0003-1682-2802)
- Rui Wang (ORCID: https://orcid.org/0000-0003-3825-3620)
- Dongfeng Yin
- Peng Jiang (ORCID: https://orcid.org/0000-0002-1032-7774)
- Yuqiang Liu (ORCID: https://orcid.org/0000-0002-0350-3071)
- Qian Li (ORCID: https://orcid.org/0000-0002-6427-3783)
- Feng Yang (ORCID: https://orcid.org/0000-0002-4760-6005)
- Xi Yang (ORCID: https://orcid.org/0000-0003-2981-3972)
- Z. B. Sun
- Dan Yang (ORCID: https://orcid.org/0000-0001-9984-7225)
Institutions
- Shihezi University (CN)
- Xinjiang Medical University (CN)
- PLA 306 Hospital (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-09-02
- DOI
- https://doi.org/10.3389/fmed.2025.1603140
- Primary Topic
- High Altitude and Hypoxia
- Type
- article
- Field-Weighted Citation Impact
- 0.00