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Introduction

  • Katarzyna A. Tarnowska
  • Zbigniew W. Ras
  • Pawel J. Jastreboff
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 685)

Abstract

Recently, there has been an increasing interest in business analytics and big data tools to understand and drive industries evolution. The healthcare industry is also interested in new methods to analyze data and provide better care. Given the wealth of data that various institutions are accumulating, it is natural to take advantage of data driven decision-making solutions. Recommender systems proved to be a valuable mean to deal with the decision problems, especially in commercial merchandising. They are of special importance nowadays, when people are facing information overload and the growth and variety of information (products, news) available on the Web frequently overwhelms individuals. It leads them, in turn, to make poor decisions and decreases their well-being. Recommender systems enable automation of some of strategies in human decision making, support their users in various processes, providing advice that is both high-quality and high-personalized. In the area of healthcare they provide valuable support for physicians treating their patients, such as the one described in [Szl15]. The potential economic benefits of applying computerized clinical decision support systems include improved efficiency in health care delivery e.g. by reducing costs as well as improved quality of care and improved patient safety.

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Katarzyna A. Tarnowska
    • 1
  • Zbigniew W. Ras
    • 1
  • Pawel J. Jastreboff
    • 2
  1. 1.Department of Computer ScienceUniversity of North Carolina at CharlotteCharlotteUSA
  2. 2.Department of OtolaryngologyEmory University School of MedicineAtlantaUSA

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