A novel method for dipper/non-dipper pattern classification in hypertensive and non-diabetic patients

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Altıkardeş Z. A., Kayikli A., Korkmaz H., Erdal H., Baba A. F., Fak A. S.

TECHNOLOGY AND HEALTH CARE, vol.27, 2019 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 27
  • Publication Date: 2019
  • Doi Number: 10.3233/thc-199006
  • Journal Name: TECHNOLOGY AND HEALTH CARE
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Marmara University Affiliated: Yes

Abstract

BACKGROUND: In the classical process, it was proven that ABPM data were the most significant attributes both by physician and ranking algorithms for dipper/non-dipper pattern classification as mentioned in our previous papers. To explore if any algorithm exists that would let the physician skip this diagnosis step is the main motivation of the study.