How Domain Engineering Can Help to Raise Adoption Rates of Artificial Intelligence in Healthcare

Markus Bertl; Toomas Klementi; Gunnar Piho; Peeter Ross; Dirk Draheim

doi:10.1007/978-3-031-48316-5_1

How Domain Engineering Can Help to Raise Adoption Rates of Artificial Intelligence in Healthcare

Markus Bertl^*
, Toomas Klementi
, Gunnar Piho
, Peeter Ross
, Dirk Draheim

^*Corresponding author for this work

Publication: Chapter in book/Conference proceeding › Contribution to conference proceedings

Abstract

Regardless of the often-claimed success of artificial intelligence (AI) and machine learning (ML), AI-based Digital Decision Support Systems (DDSSs) still suffer from low adoption rates. Much algorithmic research is done, but examples of AI bringing tangible benefits to the healthcare industry are rare. We argue that one of the reasons for low adoption rates is missing domain understanding and/or the heterogeneity of domain understanding among the DDSS developers and domain experts. To overcome this, we are working towards a methodology to utilize the Domain Engineering approach to create a shared common understanding of key concepts and relationships within the healthcare domain in a structured, formalized way. In the realm of complex interdisciplinary DDSS development within healthcare, the Domain Engineering approach can serve as a valuable instrument for bridging the gap between IT professionals and domain experts. It facilitates establishing a shared comprehension of the domain and hopefully contributes significantly to increasing the value and adoption rates of DDSSs in the clinical process. In this paper, we are proposing our work-in-progress ideas and preliminary results.

Original language	English
Title of host publication	Information Integration and Web Intelligence - 25th International Conference, iiWAS 2023, Proceedings
Subtitle of host publication	Denpasar, Bali, Indonesia, December 4–6, 2023
Editors	Pari Delir Haghighi, Eric Pardede, Gillian Dobbie, Vithya Yogarajan, Ngurah Agus Sanjaya ER, Gabriele Kotsis, Ismail Khalil
Place of Publication	Cham
Publisher	Springer
Pages	3-12
Number of pages	10
ISBN (Electronic)	9783031483165
ISBN (Print)	9783031483158
DOIs	https://doi.org/10.1007/978-3-031-48316-5_1
Publication status	Published - 2023
Externally published	Yes
Event	25th International Conference on Information Integration and Web Intelligence, iiWAS 2023 - Denpasar, Indonesia Duration: 4 Dec 2023 → 6 Dec 2023

Publication series

Series	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	14416
ISSN	0302-9743

Conference

Conference	25th International Conference on Information Integration and Web Intelligence, iiWAS 2023
Country/Territory	Indonesia
City	Denpasar
Period	4/12/23 → 6/12/23

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Artificial Intelligence (AI)
DDSSs Adoption Rates
Digital Decision Support System (DDSS)
Digital Health
Domain Engineering
User Acceptance

Access to Document

10.1007/978-3-031-48316-5_1

Cite this

Bertl, M., Klementi, T., Piho, G., Ross, P., & Draheim, D. (2023). How Domain Engineering Can Help to Raise Adoption Rates of Artificial Intelligence in Healthcare. In P. Delir Haghighi, E. Pardede, G. Dobbie, V. Yogarajan, N. A. S. ER, G. Kotsis, & I. Khalil (Eds.), Information Integration and Web Intelligence - 25th International Conference, iiWAS 2023, Proceedings: Denpasar, Bali, Indonesia, December 4–6, 2023 (pp. 3-12). Springer. https://doi.org/10.1007/978-3-031-48316-5_1

Bertl, Markus ; Klementi, Toomas ; Piho, Gunnar et al. / How Domain Engineering Can Help to Raise Adoption Rates of Artificial Intelligence in Healthcare. Information Integration and Web Intelligence - 25th International Conference, iiWAS 2023, Proceedings: Denpasar, Bali, Indonesia, December 4–6, 2023. editor / Pari Delir Haghighi ; Eric Pardede ; Gillian Dobbie ; Vithya Yogarajan ; Ngurah Agus Sanjaya ER ; Gabriele Kotsis ; Ismail Khalil. Cham : Springer, 2023. pp. 3-12 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 14416).

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Bertl, M, Klementi, T, Piho, G, Ross, P & Draheim, D 2023, How Domain Engineering Can Help to Raise Adoption Rates of Artificial Intelligence in Healthcare. in P Delir Haghighi, E Pardede, G Dobbie, V Yogarajan, NAS ER, G Kotsis & I Khalil (eds), Information Integration and Web Intelligence - 25th International Conference, iiWAS 2023, Proceedings: Denpasar, Bali, Indonesia, December 4–6, 2023. Springer, Cham, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14416, pp. 3-12, 25th International Conference on Information Integration and Web Intelligence, iiWAS 2023, Denpasar, Indonesia, 4/12/23. https://doi.org/10.1007/978-3-031-48316-5_1

How Domain Engineering Can Help to Raise Adoption Rates of Artificial Intelligence in Healthcare. / Bertl, Markus; Klementi, Toomas; Piho, Gunnar et al.
Information Integration and Web Intelligence - 25th International Conference, iiWAS 2023, Proceedings: Denpasar, Bali, Indonesia, December 4–6, 2023. ed. / Pari Delir Haghighi; Eric Pardede; Gillian Dobbie; Vithya Yogarajan; Ngurah Agus Sanjaya ER; Gabriele Kotsis; Ismail Khalil. Cham: Springer, 2023. p. 3-12 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 14416).

Publication: Chapter in book/Conference proceeding › Contribution to conference proceedings

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AU - Draheim, Dirk

PY - 2023

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N2 - Regardless of the often-claimed success of artificial intelligence (AI) and machine learning (ML), AI-based Digital Decision Support Systems (DDSSs) still suffer from low adoption rates. Much algorithmic research is done, but examples of AI bringing tangible benefits to the healthcare industry are rare. We argue that one of the reasons for low adoption rates is missing domain understanding and/or the heterogeneity of domain understanding among the DDSS developers and domain experts. To overcome this, we are working towards a methodology to utilize the Domain Engineering approach to create a shared common understanding of key concepts and relationships within the healthcare domain in a structured, formalized way. In the realm of complex interdisciplinary DDSS development within healthcare, the Domain Engineering approach can serve as a valuable instrument for bridging the gap between IT professionals and domain experts. It facilitates establishing a shared comprehension of the domain and hopefully contributes significantly to increasing the value and adoption rates of DDSSs in the clinical process. In this paper, we are proposing our work-in-progress ideas and preliminary results.

AB - Regardless of the often-claimed success of artificial intelligence (AI) and machine learning (ML), AI-based Digital Decision Support Systems (DDSSs) still suffer from low adoption rates. Much algorithmic research is done, but examples of AI bringing tangible benefits to the healthcare industry are rare. We argue that one of the reasons for low adoption rates is missing domain understanding and/or the heterogeneity of domain understanding among the DDSS developers and domain experts. To overcome this, we are working towards a methodology to utilize the Domain Engineering approach to create a shared common understanding of key concepts and relationships within the healthcare domain in a structured, formalized way. In the realm of complex interdisciplinary DDSS development within healthcare, the Domain Engineering approach can serve as a valuable instrument for bridging the gap between IT professionals and domain experts. It facilitates establishing a shared comprehension of the domain and hopefully contributes significantly to increasing the value and adoption rates of DDSSs in the clinical process. In this paper, we are proposing our work-in-progress ideas and preliminary results.

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KW - Digital Decision Support System (DDSS)

KW - Digital Health

KW - Domain Engineering

KW - User Acceptance

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Bertl M, Klementi T, Piho G, Ross P, Draheim D. How Domain Engineering Can Help to Raise Adoption Rates of Artificial Intelligence in Healthcare. In Delir Haghighi P, Pardede E, Dobbie G, Yogarajan V, ER NAS, Kotsis G, Khalil I, editors, Information Integration and Web Intelligence - 25th International Conference, iiWAS 2023, Proceedings: Denpasar, Bali, Indonesia, December 4–6, 2023. Cham: Springer. 2023. p. 3-12. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 14416). doi: 10.1007/978-3-031-48316-5_1