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001     1005412
005     20250804154811.0
024 7 _ |2 HBZ
|a HT030979475
024 7 _ |2 Laufende Nummer
|a 44020
037 _ _ |a RWTH-2025-01746
041 _ _ |a English
082 _ _ |a 330
100 1 _ |0 P:(DE-588)1361612347
|a Meyer, Lea Mareen
|b 0
|u rwth
245 _ _ |a Essays on human-AI collaboration : insights from healthcare
|c vorgelegt von Lea Mareen Meyer
|h print
260 _ _ |a Aachen
|c 2025
300 _ _ |a xvi, 182 Seiten : Illustrationen
336 7 _ |0 2
|2 EndNote
|a Thesis
336 7 _ |0 PUB:(DE-HGF)11
|2 PUB:(DE-HGF)
|a Dissertation / PhD Thesis
|b phd
|m phd
336 7 _ |2 BibTeX
|a PHDTHESIS
336 7 _ |2 DRIVER
|a doctoralThesis
336 7 _ |2 DataCite
|a Output Types/Dissertation
336 7 _ |2 ORCID
|a DISSERTATION
502 _ _ |a Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2025
|b Dissertation
|c Rheinisch-Westfälische Technische Hochschule Aachen
|d 2025
|g Fak08
|o 2025-01-31
520 3 _ |l ger
520 _ _ |a Collaboration between individuals and artificial intelligence (AI) in healthcare has become a central topic in both information system (IS) research and broader societal discussions on leveraging human skills with AI capabilities. As AI applications advance and get more involved in healthcare processes, exploring how individuals (i.e., medical staff such as physicians and nurses) and AI can collaborate most effectively is essential. This collaboration integrates human expertise and contextual understanding with AI’s precision and data processing capabilities. Combining these expertise offers the possibility to improve patient outcomes, relieve medical staff, and increase their decision-making. Despite the growing interest in human-AI collaboration, existing research mainly focuses on theoretical advancements and AI’s potential and neglects practical field tests, deployment, and interaction between individuals and AI. Consequently, AI’s potential is not sufficiently realized, and developed AI applications mismatch with practical needs, resulting in no or fragmented deployment in practice. To overcome this research gap, this thesis adopts an engaged scholarship approach. It is a promising research methodology that focuses on a participative form incorporating practitioners in the research process. Engaged scholarship is instrumental in generating a sustained and in-depth understanding of human-AI collaboration. The thesis comprises three research essays on human-AI collaboration, each offering a different perspective on the collaboration process. To ensure an ongoing knowledge transfer from research to practice and vice versa, all three research essays are informed by one AI research project deeply embedded in clinical practices to develop and implement an AI application in a hospital. In summary, this thesis contributes to existing research on human-AI collaboration by analyzing the collaboration process from multiple perspectives. This research sheds light on the dynamics and the interplay between individuals and AI, offering guidance to ensure AI’s practical relevance and deployment for healthcare practices. In doing so, this thesis provides a nuanced understanding of human-AI collaboration at the intersection between research and practice.
|l eng
591 _ _ |a Germany
653 _ 7 |a AI applications
653 _ 7 |a applied research
653 _ 7 |a healthcare
653 _ 7 |a human-AI collaboration
653 _ 7 |a hybrid collaboration
700 1 _ |0 P:(DE-82)IDM02290
|a Salge, Torsten-Oliver
|b 1
|e Thesis advisor
|u rwth
700 1 _ |0 P:(DE-82)IDM01911
|a Paluch, Stefanie
|b 2
|e Thesis advisor
|u rwth
856 4 _ |u https://digitale-objekte.hbz-nrw.de/storage2/2025/04/05/file_13/9859155.pdf
|y Table of contents
909 C O |o oai:publications.rwth-aachen.de:1005412
|p VDB
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|a RWTH Aachen
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910 1 _ |0 I:(DE-588b)36225-6
|6 P:(DE-82)IDM02290
|a RWTH Aachen
|b 1
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910 1 _ |0 I:(DE-588b)36225-6
|6 P:(DE-82)IDM01911
|a RWTH Aachen
|b 2
|k RWTH
914 1 _ |y 2025
920 1 _ |0 I:(DE-82)816410_20140620
|k 816410
|l Lehrstuhl für Innovation, Strategie und Organisation
|x 0
980 _ _ |a I:(DE-82)816410_20140620
980 _ _ |a UNRESTRICTED
980 _ _ |a VDB
980 _ _ |a phd


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