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Personalized venlafaxine dose prediction using artificial intelligence technology: a retrospective analysis based on real-world data.

Yimeng LiuZe YuXuxiao YeJinyuan ZhangXin HaoFei GaoJing YuChunhua Zhou
Published in: International journal of clinical pharmacy (2024)
We successfully developed a TabNet model to predict venlafaxine doses using real-world data. This model demonstrated substantial predictive accuracy, offering a personalized dosing regimen for venlafaxine. These findings provide valuable guidance for the clinical use of the drug.
Keyphrases
  • artificial intelligence
  • big data
  • machine learning
  • electronic health record
  • deep learning
  • data analysis
  • drug induced