Machine learning reveals CAT gene as a novel potential diagnostic and prognostic biomarker in non-small cell lung cancer

Machine learning reveals CAT gene as a novel potential diagnostic and prognostic biomarker in non-small cell lung cancer

Abstract Background Non-small cell lung cancer (NSCLC) represents one of the most prevalent forms of lung cancer, with a five-year survival rate of 21.7%. There is an urgent need to identify pertinent biomarkers to inform the diagnosis and prognosis of tumors, particularly those that can be applied...

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Bibliografiska uppgifter
Huvudupphovsmän: Yi Tian, Wen-ya Zhao, Yi-ru Liu, Wen-wen Song, Qiao-xin Lin, Yan-na Gong, Yi-ting Deng, Dian-na Gu, Ling Tian
Materialtyp: Artikel
Språk:English
Publicerad: Springer 2024-12-01
Serie:Discover Oncology
Ämnen:
Machine learning
Catalase gene
Biomarker
Aging-related genes
Age heterogeneity
Non-small cell lung cancer
Länkar:https://doi.org/10.1007/s12672-024-01670-1

Internet

https://doi.org/10.1007/s12672-024-01670-1

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