Construction of an artificial neural network diagnostic model and investigation of immune cell infiltration characteristics for idiopathic pulmonary fibrosis
LRRC17, COMP, ASPN, CRTAC1, POSTN, COL3A1, PEBP4, IL13RA2, and CA4 were determined as key feature genes for IPF. The nine feature genes in the ANN model will be extremely important for diagnosing IPF. It may be possible to use differentiated immune cells from IPF samples in comparison to normal samples as targets for immunotherapy in patients with IPF.
Authors
- Qingqing Xia (ORCID: https://orcid.org/0000-0001-5287-0639)
- Weilong Jiang (ORCID: https://orcid.org/0000-0001-8416-6080)
- Haibing Hua (ORCID: https://orcid.org/0000-0001-9346-9972)
- Huizhe Zhang (ORCID: https://orcid.org/0000-0002-6378-6982)
- Chenjing Zhu (ORCID: https://orcid.org/0000-0001-8798-6367)
- Yufeng Zhang
- Cong Wang (ORCID: https://orcid.org/0000-0002-6089-251X)
- Xiaodong Hu (ORCID: https://orcid.org/0009-0001-1001-1358)
Institutions
- Jiangyin People's Hospital (CN)
- Jiangyin Traffic Planning Survey & Design Institute (China) (CN)
- Yancheng Third People's Hospital (CN)
- Yancheng Second People's Hospital (CN)
Publication Details
- Journal
- BMC Pulmonary Medicine
- Published
- 2024-09-17
- DOI
- https://doi.org/10.1186/s12890-024-03249-6
- Citations
- 3
- Primary Topic
- Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
- Type
- article
- Field-Weighted Citation Impact
- 1.26
Funders
- Government of Jiangsu Province
- Nanjing University of Chinese Medicine
- Nanjing University