Human-centered artificial intelligence: a multidimensional approach towards real world evidence
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Author (Corporation)
Publication date
2019
Typ of student thesis
Course of study
Collections
Type
04B - Conference paper
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Parent work
ICEIS 2019. 21st International Conference on Enterprise Information Systems. Proceedings
Special issue
DOI of the original publication
Link
Series
Series number
Volume
1
Issue / Number
Pages / Duration
381-390
Patent number
Publisher / Publishing institution
Place of publication / Event location
Heraklion
Edition
Version
Programming language
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Practice partner / Client
Abstract
This study indicates the significance of a human-centered perspective in the analysis and interpretation of Real World Data. As an exemplary use-case, the construct of perceived ‘Health-related Quality of Life’ is chosen to show, firstly, the significance of Real World Data and, secondly, the associated ‘Real World Evidence’. We settled on an iterative methodology and used hermeneutics for a detailed literature analysis to outline the relevance and the need for a forward-thinking approach to deal with Real World Evidence in the life science and health care industry. The novelty of the study is its focus on a human-centered artificial intelligence, which can be achieved by using ‘System Dynamics’ modelling techniques. The outcome – a human-centered ‘Indicator Set’ can be combined with results from data-driven, AI-based analytics. With this multidimensional approach, human intelligence and artificial intelligence can be intertwined towards an enriched Real World Evidence. The developed approach considers three perspectives – the elementary, the algorithmic and – as novelty – the human-centered evidence. As conclusion, we claim that Real World Data are more valuable and applicable to achieve patient-centricity and personalization if the human-centered perspective is considered ‘by design’.
Keywords
Subject (DDC)
Event
21st International Conference on Enterprise Information Systems (ICEIS 2019)
Exhibition start date
Exhibition end date
Conference start date
03.05.2019
Conference end date
05.05.2019
Date of the last check
ISBN
978-989-758-372-8
ISSN
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
Review
Peer review of the complete publication
Open access category
Closed
License
Citation
Schneider, B., Asprion, P., & Grimberg, F. (2019). Human-centered artificial intelligence: a multidimensional approach towards real world evidence. In J. Filipe, M. Smialek, A. Brodsky, & S. Hammoudi (Eds.), ICEIS 2019. 21st International Conference on Enterprise Information Systems. Proceedings (Vol. 1, pp. 381–390). https://doi.org/10.5220/0007715503810390