A new application of machine learning in health care

Kaj Mikael Björk, Emil Eirola, Yoan Miche, Amaury Lendasse

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

In our ever more complex world, the field of analytics has dramatically increased its importance. Gut feeling is no longer sufficient in decision making, but intuition has to be combined with support from the huge amount of data available today. Even if the amount of data is enormous, the quality of the data is not always good. Problems arise in at least two situations: i) the data is imprecise by nature and ii) the data is incomplete (or there are missing parts in the data set). Both situations are problematic and need to be addressed appropriately. If these problems are solved, applications are to be found in various interesting fields. We aim at achieving significant methodology development as well as creative solutions in the domain of medicine, information systems and risk management. This paper sets focus especially on missing data problems in the field of medicine when presenting a new project in its very first phase.

Original languageEnglish
Title of host publicationProceedings of the 9th ACM International Conference on Pervasive Technologies Related to Assistive Environments, PETRA 2016
PublisherACM - Association for Computing Machinery
Publication date29.06.2016
Article number49
ISBN (Electronic)978-1-4503-4337-4
DOIs
Publication statusPublished - 29.06.2016
MoE publication typeA4 Article in conference proceedings
Event9th ACM International Conference on Pervasive Technologies Related to Assistive Environments, PETRA 2016 - Corfu, Greece
Duration: 29.06.201601.07.2016

Keywords

  • 512 Business and Management

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    Björk, K. M., Eirola, E., Miche, Y., & Lendasse, A. (2016). A new application of machine learning in health care. In Proceedings of the 9th ACM International Conference on Pervasive Technologies Related to Assistive Environments, PETRA 2016 [49] ACM - Association for Computing Machinery. https://doi.org/10.1145/2910674.2935861