Identifying patients with familial chylomicronemia syndrome using fcs score-based data mining methods

HIGHLIGHTS

• who: u00c1kos Nu00e9meth and collaborators from the Division of Metabolic Disorders, Department of Internal Medicine, Faculty of Medicine, University of have published the research: Identifying Patients with Familial Chylomicronemia Syndrome Using FCS Score-Based Data Mining Methods, in the Journal: (JOURNAL) of 25/07/2022
• what: The authors aimed to identify patients either the proposed by Moulin et_al or with and assessed the diagnostic applicability of the Methods: Analyzing medical records of 1 342 124 patients the of each patient was calculated. on the of previously diagnosed patients the authors trained machine learning models to . . .
  

   

  

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