Predicting lapatinib dose regimen using machine learning and deep learning techniques based on a real-world study

HIGHLIGHTS

• who: Ze Yu from the Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai, China have published the article: Predicting Lapatinib Dose Regimen Using Machine Learning and Deep Learning Techniques Based on a Real-World Study, in the Journal: (JOURNAL)
• how: As a novel deep learning architecture the authors implemented the TabNet model exactly as described in Arik and Pfister used a sparsemax attention and included the sparsification term in the loss function . In Table 1 the authors presented the predictive performance of 12 models. The authors applied TabNet super TML . . .
  

   

  

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