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  • 标题:Immune gene prognostic signature for disease free survival of gastric cancer: Translational research of an artificial intelligence survival predictive system
  • 本地全文:下载
  • 作者:Zhiqiao Zhang ; Tingshan He ; Liwen Huang
  • 期刊名称:Computational and Structural Biotechnology Journal
  • 印刷版ISSN:2001-0370
  • 出版年度:2021
  • 卷号:19
  • 页码:2329-2346
  • DOI:10.1016/j.csbj.2021.04.025
  • 出版社:Computational and Structural Biotechnology Journal
  • 摘要:The progress of artificial intelligence algorithms and massive data provide new ideas and choices for individual mortality risk prediction for cancer patients. The current research focused on depict immune gene related regulatory network and develop an artificial intelligence survival predictive system for disease free survival of gastric cancer. Multi-task logistic regression algorithm, Cox survival regression algorithm, and Random survival forest algorithm were used to develop the artificial intelligence survival predictive system. Nineteen transcription factors and seventy immune genes were identified to construct a transcription factor regulatory network of immune genes. Multivariate Cox regression identified fourteen immune genes as prognostic markers. These immune genes were used to construct a prognostic signature for gastric cancer. Concordance indexes were 0.800, 0.809, and 0.856 for 1-, 3- and 5- year survival. An interesting artificial intelligence survival predictive system was developed based on three artificial intelligence algorithms for gastric cancer. Gastric cancer patients with high risk score have poor survival than patients with low risk score. The current study constructed a transcription factor regulatory network and developed two artificial intelligence survival prediction tools for disease free survival of gastric cancer patients. These artificial intelligence survival prediction tools are helpful for individualized treatment decision.
  • 关键词:Immune gene ; Transcription factor ; Gastric cancer ; Disease free survival ; Prognostic signature
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