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Case Study: IBM Watson Analytics Cloud Platform as Analytics-as-a-Service System for Heart Failure Early Detection

Author

Listed:
  • Gabriele Guidi

    (Department of Information Engineering Unversità degli Studi di Firenze, v. S. Marta, 3-50139 Firenze, Italy)

  • Roberto Miniati

    (Department of Information Engineering Unversità degli Studi di Firenze, v. S. Marta, 3-50139 Firenze, Italy)

  • Matteo Mazzola

    (Department of Information Engineering Unversità degli Studi di Firenze, v. S. Marta, 3-50139 Firenze, Italy)

  • Ernesto Iadanza

    (Department of Information Engineering Unversità degli Studi di Firenze, v. S. Marta, 3-50139 Firenze, Italy)

Abstract

In the recent years the progress in technology and the increasing availability of fast connections have produced a migration of functionalities in Information Technologies services, from static servers to distributed technologies. This article describes the main tools available on the market to perform Analytics as a Service (AaaS) using a cloud platform. It is also described a use case of IBM Watson Analytics, a cloud system for data analytics, applied to the following research scope: detecting the presence or absence of Heart Failure disease using nothing more than the electrocardiographic signal, in particular through the analysis of Heart Rate Variability. The obtained results are comparable with those coming from the literature, in terms of accuracy and predictive power. Advantages and drawbacks of cloud versus static approaches are discussed in the last sections.

Suggested Citation

  • Gabriele Guidi & Roberto Miniati & Matteo Mazzola & Ernesto Iadanza, 2016. "Case Study: IBM Watson Analytics Cloud Platform as Analytics-as-a-Service System for Heart Failure Early Detection," Future Internet, MDPI, vol. 8(3), pages 1-16, July.
    • Handle: RePEc:gam:jftint:v:8:y:2016:i:3:p:32-:d:73883
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    Citations

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    Cited by:

    1. Dino Giuli, 2018. "Ecosystemic Evolution Fed by Smart Systems," Future Internet, MDPI, vol. 10(3), pages 1-3, March.
    2. Carlos de las Heras-Pedrosa & Pablo Sánchez-Núñez & José Ignacio Peláez, 2020. "Sentiment Analysis and Emotion Understanding during the COVID-19 Pandemic in Spain and Its Impact on Digital Ecosystems," IJERPH, MDPI, vol. 17(15), pages 1-22, July.

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