Data science in healthcare: benefits, challenges and opportunities

Ziawasch Abedjan, Nozha Boujemaa, Stuart Campbell, Patricia Casla, Supriyo Chatterjea, Sergio Consoli, Cristobal Costa-Soria, Paul Czech, Marija Despenic, Chiara Garattini, Dirk Hamelinck, Adrienne Heinrich, Wessel Kraaij, Jacek Kustra, Aizea Lojo, Marga Martin Sanchez, Miguel A. Mayer, Matteo Melideo, Ernestina Menasalvas, Frank Moller AarestrupElvira Narro Artigot, Milan Petković, Diego Reforgiato Recupero, Alejandro Rodriguez Gonzalez, Gisele Roesems Kerremans, Roland Roller, Mario Romao, Stefan Ruping, Felix Sasaki, Wouter Spek, Nenad Stojanovic, Jack Thoms, Andrejs Vasiljevs, Wilfried Verachtert, Roel Wuyts

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

1 Citation (Scopus)

Abstract

The advent of digital medical data has brought an exponential increase in information available for each patient, allowing for novel knowledge generation methods to emerge. Tapping into this data brings clinical research and clinical practice closer together, as data generated in ordinary clinical practice can be used towards rapid-learning healthcare systems, continuously improving and personalizing healthcare. In this context, the recent use of Data Science technologies for healthcare is providing mutual benefits to both patients and medical professionals, improving prevention and treatment for several kinds of diseases. However, the adoption and usage of Data Science solutions for healthcare still require social capacity, knowledge and higher acceptance. The goal of this chapter is to provide an overview of needs, opportunities, recommendations and challenges of using (Big) Data Science technologies in the healthcare sector. This contribution is based on a recent whitepaper (http://www.bdva.eu/sites/default/files/Big%20Data%20Technologies%20in%20Healthcare.pdf) provided by the Big Data Value Association (BDVA) (http://www.bdva.eu/), the private counterpart to the EC to implement the BDV PPP (Big Data Value PPP) programme, which focuses on the challenges and impact that (Big) Data Science may have on the entire healthcare chain.

Original languageEnglish
Title of host publicationData Science for Healthcare
Subtitle of host publicationMethodologies and Applications
EditorsS. Consoli, D. Reforgiato Recupero, M. Petković
Place of PublicationCham
PublisherSpringer
Pages3-38
Number of pages36
ISBN (Electronic)978-3-030-05249-2
ISBN (Print)978-3-030-05248-5
DOIs
Publication statusPublished - 1 Jan 2019

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    Abedjan, Z., Boujemaa, N., Campbell, S., Casla, P., Chatterjea, S., Consoli, S., Costa-Soria, C., Czech, P., Despenic, M., Garattini, C., Hamelinck, D., Heinrich, A., Kraaij, W., Kustra, J., Lojo, A., Sanchez, M. M., Mayer, M. A., Melideo, M., Menasalvas, E., ... Wuyts, R. (2019). Data science in healthcare: benefits, challenges and opportunities. In S. Consoli, D. Reforgiato Recupero, & M. Petković (Eds.), Data Science for Healthcare: Methodologies and Applications (pp. 3-38). Springer. https://doi.org/10.1007/978-3-030-05249-2_1