Use of machine learning to identify patients at risk of sub-optimal adherence: study based on real-world data from 10,929 children using a connected auto-injector device

HIGHLIGHTS

• who: Amalia Spataru from the Box, CE Leiden, The Netherlands have published the article: Use of machine learning to identify patients at risk of sub-optimal adherence: study based on real-world data from 10,929 children using a connected auto-injector device, in the Journal: (JOURNAL)
• what: The aforementioned commercial service had received all necessary legal approvals to allow secondary research purposes. To obtain the typical thresholds used by the model for distinguishing between the two classes, local interpretation techniques were applied on 10 randomly chosen instances of the optimal and sub-optimal classes . . .
  

   

  

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