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Reasoning and causal inference regarding surgical options for patients with low-grade gliomas using machine learning: A SEER-based study.

Enzhao ZhuWeizhong ShiZhihao ChenJiayi WangPu AiXiao WangMin ZhuZiqin XuLingxiao XuXueyi SunJingyu LiuXuetong XuDan Shan
Published in: Cancer medicine (2023)
This is the first study to infer the individual treatment effect, make treatment recommendation, and guide surgical options through deep learning approach in LGG research. Through causal inference, we found that heterogeneous responses to STR and GTR exist in patients with LGG. Visualization of the model yielded several factors that contribute to treatment heterogeneity, which are worthy of further discussion.
Keyphrases
  • low grade
  • deep learning
  • high grade
  • single cell
  • machine learning
  • combination therapy
  • artificial intelligence