Using minimum redundancy maximum relevance algorithm to select minimal sets of heart rate variability parameters for atrial fibrillation detection

HIGHLIGHTS

• who: Szymon Buś and collaborators from the Institute of Electronic Systems, Faculty of Electronics and Information Technology, Warsaw University of have published the research work: Using Minimum Redundancy Maximum Relevance Algorithm to Select Minimal Sets of Heart Rate Variability Parameters for Atrial Fibrillation Detection, in the Journal: (JOURNAL) of 11/07/2022
• what: The authors aimed to study the impact of the selection of HRV parameters (features in terms of ML) employed as inputs in ML algorithms for distinguishing AF from SR. To study the effects of minimal sets composed of other HRV features, the . . .
  

   

  

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