Development of a prognostic prediction signature for idiopathic pulmonary fibrosis by integrating multiple programmed cell death-related genes and machine learning algorithms Article Swipe

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Jingyang Sun , Rongxuan Jiang , Meng Li , Qian Zhai , Niuniu Dong , Huanhuan Dong , Guangjian Zhang , Yanpeng Zhang ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.21037/jtd-2024-2173

The prognostic signature based on PCD-related genes provides new biomarkers for the prognostic assessment of IPF, and has high predictive accuracy. Additionally, the identified potential drugs offer new directions for the treatment of IPF, laying the foundation for future individualized therapies.

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Type: article
Language: en
Landing Page: https://doi.org/10.21037/jtd-2024-2173
OA Status: diamond
Cited By: 1
OpenAlex ID: https://openalex.org/W4414615670

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OpenAlex ID: https://openalex.org/W4414615670

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DOI: https://doi.org/10.21037/jtd-2024-2173

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Title: Development of a prognostic prediction signature for idiopathic pulmonary fibrosis by integrating multiple programmed cell death-related genes and machine learning algorithms

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Type: article

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Language: en

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Publication year: 2025

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Publication date: 2025-09-01

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Authors: Jingyang Sun, Rongxuan Jiang, Meng Li, Qian Zhai, Niuniu Dong, Huanhuan Dong, Guangjian Zhang, Yanpeng Zhang

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Landing page: https://doi.org/10.21037/jtd-2024-2173

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OA status: diamond

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OA URL: https://doi.org/10.21037/jtd-2024-2173

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Cited by: 1

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Citations by year (recent): 2025: 1

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