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Predicting the Outcome of Antihypertensive Therapy Using Knowledge Mining

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Handbook of Medical and Healthcare Technologies

Abstract

Arterial hypertension represents the most common non-communicable disease of our time. The prevalence of hypertension varies according to gender and age criteria, but also depends on the geographical, ethnic and racial factors and has the character of an epidemic [1]. Among the adult population, arterial hypertension is considered as one of leading risk factors for the development of atherosclerosis. In a number of epidemiological studies, elevated blood pressure has been identified as a risk factor for heart failure, cerebrovascular disease, peripheral artery disease, renal failure, and, more recently, atrial fibrillation [2, 3].

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Authors and Affiliations

  1. Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia

    Srdjan Sladojevic & Dubravko Culibrk

  2. Clinic of Cardiology, Institute of Cardiovascular Diseases Vojvodina, Sremska Kamenica, Serbia

    Miroslava Sladojevic, Katica Pavlovic & Nada Cemerlic-Adjic

Authors
  1. Srdjan Sladojevic
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  2. Miroslava Sladojevic
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  3. Katica Pavlovic
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  4. Nada Cemerlic-Adjic
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  5. Dubravko Culibrk
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Correspondence to Dubravko Culibrk .

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Editors and Affiliations

  1. Florida Atlantic University Dept. of Computer Science & Engineering, Boca Raton, Florida, USA

    Borko Furht

  2. Department of Computer Science and Engineering, Florida Atlantic University, Boca Raton, Florida, USA

    Ankur Agarwal

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Sladojevic, S., Sladojevic, M., Pavlovic, K., Cemerlic-Adjic, N., Culibrk, D. (2013). Predicting the Outcome of Antihypertensive Therapy Using Knowledge Mining. In: Furht, B., Agarwal, A. (eds) Handbook of Medical and Healthcare Technologies. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8495-0_9

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  • DOI: https://doi.org/10.1007/978-1-4614-8495-0_9

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