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Bergquist, M., Rolandsson, B., Gryska, E., Laesser, M., Hoefling, N., Heckemann, R., . . . Björkman-Burtscher, I. M. (2024). Trust and stakeholder perspectives on the implementation of AI tools in clinical radiology. European Radiology, 34(1), 338-347
Open this publication in new window or tab >>Trust and stakeholder perspectives on the implementation of AI tools in clinical radiology
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2024 (English)In: European Radiology, ISSN 0938-7994, E-ISSN 1432-1084, Vol. 34, no 1, p. 338-347Article in journal (Refereed) Published
Abstract [en]

Objectives: To define requirements that condition trust in artificial intelligence (AI) as clinical decision support in radiology from the perspective of various stakeholders and to explore ways to fulfil these requirements.

Methods: Semi-structured interviews were conducted with twenty-five respondents—nineteen directly involved in the development, implementation, or use of AI applications in radiology and six working with AI in other areas of healthcare. We designed the questions to explore three themes: development and use of AI, professional decision-making, and management and organizational procedures connected to AI. The transcribed interviews were analysed in an iterative coding process from open coding to theoretically informed thematic coding.

Results: We identified four aspects of trust that relate to reliability, transparency, quality verification, and inter-organizational compatibility. These aspects fall under the categories of substantial and procedural requirements.

Conclusions: Development of appropriate levels of trust in AI in healthcare is complex and encompasses multiple dimensions of requirements. Various stakeholders will have to be involved in developing AI solutions for healthcare and radiology to fulfil these requirements. Clinical relevance statement: For AI to achieve advances in radiology, it must be given the opportunity to support, rather than replace, human expertise. Support requires trust. Identification of aspects and conditions for trust allows developing AI implementation strategies that facilitate advancing the field.

Key Points:

• Dimensions of procedural and substantial demands that need to be fulfilled to foster appropriate levels of trust in AI in healthcare are conditioned on aspects related to reliability, transparency, quality verification, and inter-organizational compatibility.  

• Creating the conditions for trust to emerge requires the involvement of various stakeholders, who will have to compensate the problem’s inherent complexity by finding and promoting well-defined solutions. © 2023, The Author(s).

Place, publisher, year, edition, pages
Heidelberg: Springer, 2024
Keywords
Artificial intelligence, Clinical decision support systems, Organizations, Radiology, Trust
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:hh:diva-51943 (URN)10.1007/s00330-023-09967-5 (DOI)37505245 (PubMedID)2-s2.0-85175105814 (Scopus ID)
Funder
Region Västra Götaland, 940050
Available from: 2023-11-15 Created: 2023-11-15 Last updated: 2024-01-17Bibliographically approved
Rajabi, E., Nowaczyk, S., Pashami, S., Bergquist, M., Ebby, G. S. & Wajid, S. (2023). A Knowledge-Based AI Framework for Mobility as a Service. Sustainability, 15(3), Article ID 2717.
Open this publication in new window or tab >>A Knowledge-Based AI Framework for Mobility as a Service
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2023 (English)In: Sustainability, E-ISSN 2071-1050, Vol. 15, no 3, article id 2717Article in journal (Refereed) Published
Abstract [en]

Mobility as a Service (MaaS) combines various modes of transportation to present mobility services to travellers based on their transport needs. This paper proposes a knowledge-based framework based on Artificial Intelligence (AI) to integrate various mobility data types and provide travellers with customized services. The proposed framework includes a knowledge acquisition process to extract and structure data from multiple sources of information (such as mobility experts and weather data). It also adds new information to a knowledge base and improves the quality of previously acquired knowledge. We discuss how AI can help discover knowledge from various data sources and recommend sustainable and personalized mobility services with explanations. The proposed knowledge-based AI framework is implemented using a synthetic dataset as a proof of concept. Combining different information sources to generate valuable knowledge is identified as one of the challenges in this study. Finally, explanations of the proposed decisions provide a criterion for evaluating and understanding the proposed knowledge-based AI framework. © 2023 by the authors.

Place, publisher, year, edition, pages
Basel: MDPI, 2023
Keywords
mobility as a service, knowledge-based, explainability
National Category
Computer Sciences
Research subject
Smart Cities and Communities
Identifiers
urn:nbn:se:hh:diva-49970 (URN)10.3390/su15032717 (DOI)000929663500001 ()2-s2.0-85148043364 (Scopus ID)
Funder
Knowledge Foundation, 20180181
Available from: 2023-02-14 Created: 2023-02-14 Last updated: 2023-08-21Bibliographically approved
Hoveskog, M., Holmén, M., Ernest, A. & Bergquist, M. (2023). Mobilizing Service Ecosystems for Sustainability – the Case of Polestar. In: Abel Diaz Gonzalez; Juliette Koning; Nancy Bocken (Ed.), NBM 2023: Proceedings of the 8th International Conference on New Business Models. Paper presented at 8th International Conference on New Business Models (NBM2023), Building partnerships for more sustainable, resilient and regenerative business models, Maastricht, The Netherlands, June 22-23, 2023. Maastricht: Maastricht University Press
Open this publication in new window or tab >>Mobilizing Service Ecosystems for Sustainability – the Case of Polestar
2023 (English)In: NBM 2023: Proceedings of the 8th International Conference on New Business Models / [ed] Abel Diaz Gonzalez; Juliette Koning; Nancy Bocken, Maastricht: Maastricht University Press , 2023Conference paper, Oral presentation with published abstract (Refereed)
Place, publisher, year, edition, pages
Maastricht: Maastricht University Press, 2023
Keywords
Service ecosystems, electric vehicles, entrepreneurial experimentation, legitimation, resource mobilization, knowledge development, market formation
National Category
Business Administration
Research subject
Smart Cities and Communities
Identifiers
urn:nbn:se:hh:diva-51142 (URN)10.26481/mup.2302 (DOI)
Conference
8th International Conference on New Business Models (NBM2023), Building partnerships for more sustainable, resilient and regenerative business models, Maastricht, The Netherlands, June 22-23, 2023
Projects
OSMaaS
Funder
Knowledge Foundation
Available from: 2023-06-29 Created: 2023-06-29 Last updated: 2023-07-05Bibliographically approved
Ali Fareedi, A., Ismail, M., Ghazawneh, A., Bergquist, M. & Ortiz-Rodriguez, F. (2023). The Utilization of Artificial Intelligence for Developing Autonomous Social Robots within Health Information Systems. In: Tiwari, Sanju et al. (Ed.), CEUR Workshop Proceedings: . Paper presented at Joint of the 2nd International Workshop on Knowledge Graph Generation From Text and the 1st International BiKE Challenge, TEXT2KG 2023 and BiKE 2023, Hersonissos, Greece, 29 May, 2023 (pp. 34-50). CEUR-WS, 3447
Open this publication in new window or tab >>The Utilization of Artificial Intelligence for Developing Autonomous Social Robots within Health Information Systems
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2023 (English)In: CEUR Workshop Proceedings / [ed] Tiwari, Sanju et al., CEUR-WS , 2023, Vol. 3447, p. 34-50Conference paper, Published paper (Refereed)
Abstract [en]

This study focuses on using AI systems, specifically conversational agents (CAs), to improve information flow during peak hours in healthcare emergency departments (EDs). We customized a Cross Industry Standard Process for Data Mining CRISP-DM approach to a CRISP-Knowledge graph (CRISP-KG) for overall design research. We use a knowledge graph approach to create an intelligent knowledge base (KBs) for CAs, which can enhance their reasoning, knowledge management, and context awareness abilities. We employ a collaborative methodology and ontology design patterns to develop a formal ontological model. Our goal is to build intelligent KBs for CAs that can interact with end-users and improve care quality in EDs, using Semantic Web Rule Language (SWRL) for inference. The KG approach can assist healthcare practitioners and patients in managing information flow more efficiently in EDs, ultimately improving care outcomes. © 2023 CEUR-WS. All rights reserved.

Place, publisher, year, edition, pages
CEUR-WS, 2023
Keywords
Conversational Agents (CAs), CRISP-KG, ED, Knowledge Management (KM), SWRL
National Category
Computer Sciences
Identifiers
urn:nbn:se:hh:diva-51637 (URN)2-s2.0-85169129710 (Scopus ID)
Conference
Joint of the 2nd International Workshop on Knowledge Graph Generation From Text and the 1st International BiKE Challenge, TEXT2KG 2023 and BiKE 2023, Hersonissos, Greece, 29 May, 2023
Available from: 2023-09-20 Created: 2023-09-20 Last updated: 2023-09-20Bibliographically approved
Ågerfalk, P. J., Axelsson, K. & Bergquist, M. (2022). Addressing climate change through stakeholder-centric information systems research: A Scandinavian approach for the masses. International Journal of Information Management, 63, Article ID 102447.
Open this publication in new window or tab >>Addressing climate change through stakeholder-centric information systems research: A Scandinavian approach for the masses
2022 (English)In: International Journal of Information Management, ISSN 0268-4012, E-ISSN 1873-4707, Vol. 63, article id 102447Article in journal (Refereed) Published
Abstract [en]

In this paper, we present three current research projects that explore how digital transformation can be a positive force to help address the causes and mitigate the consequences of climate change. Drawing on the Scandinavian approach to information systems (IS), we advocate a stakeholder-centric approach that can help inform the climate change discourse and assist in developing green digital practices and services. Finally, we propose a research agenda stating that green IS researchers need to engage in co-creative collaborative research and that green IS research should focus on normative design theory, design principles, and actual designs. © 2021 The Authors

Place, publisher, year, edition, pages
Oxford: Elsevier, 2022
Keywords
Climate change, Green IS, IS research, Scandinavian approach, Smart services, Stakeholder-centric, Sustainable development
National Category
Ecology
Identifiers
urn:nbn:se:hh:diva-46033 (URN)10.1016/j.ijinfomgt.2021.102447 (DOI)000794036000018 ()2-s2.0-85118739414 (Scopus ID)
Available from: 2021-12-06 Created: 2021-12-06 Last updated: 2023-08-21Bibliographically approved
Rajabi, E., Nowaczyk, S., Pashami, S. & Bergquist, M. (2022). An Explainable Knowledge-based AI Framework for Mobility as a Service. In: Proceedings of the International Conference on Software Engineering and Knowledge Engineering: . Paper presented at 34th International Conference on Software Engineering and Knowledge Engineering, SEKE 2022; KSIR Virtual Conference CenterPittsburgh; United States; 1 July 2022 through 10 July 2022 (pp. 312-316). Skokie, IL: Knowledge Systems Institute
Open this publication in new window or tab >>An Explainable Knowledge-based AI Framework for Mobility as a Service
2022 (English)In: Proceedings of the International Conference on Software Engineering and Knowledge Engineering, Skokie, IL: Knowledge Systems Institute, 2022, p. 312-316Conference paper, Published paper (Refereed)
Abstract [en]

Mobility as a Service (MaaS) is a relatively new domain where new types of knowledge systems have recently emerged. It combines various modes of transportation and different kinds of data to present personalized services to travellers based on transport needs. A knowledge-based framework based on Artificial Intelligence (AI) is proposed in this paper to integrate, analyze, and process different types of mobility data. The framework includes a knowledge acquisition process to extract and structure data from various sources, including mobility experts and add new information to a knowledge base. The role of AI in this framework is to aid in automatically discovering knowledge from various data sets and recommend efficient and personalized mobility services with explanations. A scenario is also presented to demonstrate the interaction of the proposed framework’s modules.

Place, publisher, year, edition, pages
Skokie, IL: Knowledge Systems Institute, 2022
Series
Proceedings of the International Conference on Software Engineering and Knowledge Engineering, E-ISSN 2325-9000 ; 2022
Keywords
Acquisition process, Data set, Knowledge based, Knowledge based framework, Knowledge system, Mobility datum, Mobility service, Personalized service, Structure data
National Category
Computer Systems
Research subject
Smart Cities and Communities
Identifiers
urn:nbn:se:hh:diva-48498 (URN)10.18293/SEKE2022-0020 (DOI)2-s2.0-85137156006 (Scopus ID)9781891706547 (ISBN)1891706543 (ISBN)
Conference
34th International Conference on Software Engineering and Knowledge Engineering, SEKE 2022; KSIR Virtual Conference CenterPittsburgh; United States; 1 July 2022 through 10 July 2022
Available from: 2022-10-19 Created: 2022-10-19 Last updated: 2022-12-05Bibliographically approved
Ali Fareedi, A., Ghazawneh, A. & Bergquist, M. (2022). Artificial Intelligence Agents and Knowledge Acquisition in Health Information System. In: MCIS 2022 Proceedings: . Paper presented at The 14th Mediterranean Conference on Information Systems (MCIS), Catanzaro, Italy, October 14-15, 2022. , Article ID 8.
Open this publication in new window or tab >>Artificial Intelligence Agents and Knowledge Acquisition in Health Information System
2022 (English)In: MCIS 2022 Proceedings, 2022, article id 8Conference paper, Published paper (Refereed)
Abstract [en]

This research work highlights the need for AI-powered applications and their usages for the optimization of information flow processes in the medical sector, from the perspective of how AI-agents can impact human-machine interaction (HCI) for acquiring relevant and necessary information in emergency department (ED). This study investigates how AI-agents can be applied to manage situations of patient related unexpected experiences, such as long waiting times, overcrowding issues, and high number of patients leaving without being diagnosed. For knowledge acquisition, we incorporated modelling workshop techniques for gathering domain information from the domain experts in the context of emergency department in Karolinska Hospital, Solna, Stockholm, Sweden, and for designing the AI-agent utilizing NLP techniques. We discuss how the proposed solution can be used as an assistant to healthcare practitioners and workers to improve medical assistance in various medical procedures to increase flow and to reduce workloads and anxiety levels. The implementation part of this work is based on the natural language processing (NLP) techniques that help to develop the intelligent behavior for information acquisition and its retrieval in a natural way to support patients/relatives’ communication with the healthcare organization efficiently and in a natural way.

Keywords
AI agents, Health Information Systems, human-machine interaction, NLP
National Category
Information Systems
Research subject
Health Innovation
Identifiers
urn:nbn:se:hh:diva-50151 (URN)
Conference
The 14th Mediterranean Conference on Information Systems (MCIS), Catanzaro, Italy, October 14-15, 2022
Available from: 2023-03-22 Created: 2023-03-22 Last updated: 2023-04-19Bibliographically approved
Bergquist, M. & Rolandsson, B. (2022). Exploring ADM in Clinical Decision-Making: Healthcare experts encountering digital automation (1ed.). In: Sarah Pink; Martin Berg; Deborah Lupton; Minna Ruckenstein (Ed.), Everyday Automation: Experiencing and Anticipating Emerging Technologies (pp. 140-153). London: Routledge
Open this publication in new window or tab >>Exploring ADM in Clinical Decision-Making: Healthcare experts encountering digital automation
2022 (English)In: Everyday Automation: Experiencing and Anticipating Emerging Technologies / [ed] Sarah Pink; Martin Berg; Deborah Lupton; Minna Ruckenstein, London: Routledge, 2022, 1, p. 140-153Chapter in book (Refereed)
Abstract [en]

This chapter investigates how healthcare experts engage in the development of Automated Decision Making (ADM), and how their discretionary work unfolds through the participation in designing ADM applications in different use contexts. Drawing on semi-structured interviews, the chapter theorises discretionary work by showing how institutionalised demands for accountability and accuracy forge the healthcare experts’ delegation of decisions using algorithms. Contrary to research claiming that ADM is about to outperform healthcare experts and make the need for clinical reasoning dispensable, the study shows that the introduction of ADM raises new demands for expertise and human accountability, whereby ADM is integrated into an existing professional practice of exploration. © 2022 selection and editorial matter, Sarah Pink, Martin Berg, Deborah Lupton, Minna Ruckenstein.

Place, publisher, year, edition, pages
London: Routledge, 2022 Edition: 1
National Category
Information Systems Nursing
Identifiers
urn:nbn:se:hh:diva-49140 (URN)10.4324/9781003170884-12 (DOI)2-s2.0-85141318107 (Scopus ID)9780367773403 (ISBN)9780367773380 (ISBN)9781003170884 (ISBN)
Note

OA funder: Malmö University Data Society

Available from: 2023-01-10 Created: 2023-01-10 Last updated: 2023-01-10Bibliographically approved
Gonçalves, D., Bergquist, M., Alänge, S. & Bunk, R. (2022). How Digital Tools Align with Organizational Agility and Strengthen Digital Innovation in Automotive Startups. In: : . Paper presented at CENTERIS - International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist - International Conference on Health and Social Care Information Systems and Technologies 2021, Braga, Portugal, 13-15 October, 2021 (pp. 107-116). Amsterdam: Elsevier, 196
Open this publication in new window or tab >>How Digital Tools Align with Organizational Agility and Strengthen Digital Innovation in Automotive Startups
2022 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Digital tools can be an enabler for automotive startups to strengthen their digital innovation capability. Still, few empirical studies describe how automotive startups apply digital tools to do this. Digital innovation capability is essential for survival in a volatile global digital marketplace. Therefore, we conducted a qualitative study based on 23 interviews with nine global automotive startups to understand how they apply digital tools to strengthen their digital innovation. The results showed that automotive startups use cloud services almost exclusively for their business. We conclude that startups choose to use digital tools as SaaS to strengthen their organizational agility and digital innovation initiatives. It harmonizes with their agile culture, effectively enabling innovation collaborations between employees internally and with external actors enabling rapidness to market. SaaS providers' startup programs enabled startups to remain focused on their innovation initiatives and not worry about scalability since the solutions scaled from the start. © 2021 Elsevier B.V. All rights reserved.

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2022. p. 10
Series
Procedia Computer Science, E-ISSN 1877-0509 ; 196
Keywords
Digital Tools, Organizational Agility, Digital Innovation Capability, Agile Culture, Automotive Startups
National Category
Information Systems, Social aspects
Identifiers
urn:nbn:se:hh:diva-46246 (URN)10.1016/j.procs.2021.11.079 (DOI)2-s2.0-85122895914 (Scopus ID)
Conference
CENTERIS - International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist - International Conference on Health and Social Care Information Systems and Technologies 2021, Braga, Portugal, 13-15 October, 2021
Available from: 2022-01-26 Created: 2022-01-26 Last updated: 2023-09-12Bibliographically approved
Gonçalves, D. & Bergquist, M. (2022). How startups utilize organizational adaptability in digital innovation. In: Proceedings of the 55th Hawaii International Conference on System Sciences: . Paper presented at The 55th Hawaii International Conference on System Sciences, HICSS-55, virtual, 5-7 January, 2022 (pp. 5285-5294). Manoa, Hawaii: University of Hawai'i Press
Open this publication in new window or tab >>How startups utilize organizational adaptability in digital innovation
2022 (English)In: Proceedings of the 55th Hawaii International Conference on System Sciences, Manoa, Hawaii: University of Hawai'i Press, 2022, , p. 10p. 5285-5294Conference paper, Published paper (Refereed)
Abstract [en]

In a global digital market, startups must have the capability to handle apprehension of knowledge and utilization of knowledge efficiently to quickly adapt to new realities as these emerge, given their limited resources—this regardless of whether it is customer needs or other events that affect the market. However, we do not know how startups quickly change course and adapt to stay competitive in the market. Therefore, we conducted a qualitative study based on 23 interviews with nine globally active automotive startups to understand startups' fast adaptability and how it impacts their digital innovation capability. The results show that startups with an organizational agility capability efficiently handle the transition between all four stages of innovative thinking. We conclude that dealing simultaneously with a problem from several different perspectives accelerates the apprehension of knowledge through concrete experience and abstract thinking; experimenting with new solutions develops new insights and knowledge.

Place, publisher, year, edition, pages
Manoa, Hawaii: University of Hawai'i Press, 2022. p. 10
Keywords
Organizational Agility, Organizational Adaptability, Framework for Creative Problem-Solving Styles, Digital Innovation, Startups
National Category
Information Systems, Social aspects
Identifiers
urn:nbn:se:hh:diva-46245 (URN)10.24251/HICSS.2022.644 (DOI)978-0-9981331-5-7 (ISBN)
Conference
The 55th Hawaii International Conference on System Sciences, HICSS-55, virtual, 5-7 January, 2022
Available from: 2022-01-26 Created: 2022-01-26 Last updated: 2023-02-15Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-6453-3653

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