Integrating Participatory Social Innovation Into Requirements Engineering for AI Health Care Solutions: Case Study.

Carina Dantas^1,2, Miriam Cabrita¹, Maciej Bobowicz³, Harm Op den Akker¹, Xavier Rafael-Palou⁴, Tuukka Hakkarainen⁵, Ira Haavisto⁵, Fredrik Strand⁶, Luis Marti-Bonmati⁷, Eugen Divjak⁸, Gordana Ivanac⁸, Smriti Joshi⁹, Richard Osuala⁹, Stefanie Charalambous¹⁰, Apostolia Tsirikoglou⁶, Gloria Ribas⁷, Oliver Díaz⁹, Ana Sofia Carvalho², Elísio Costa¹¹

¹SHINE 2Europe (Portugal), Rua Câmara Pestana Lote 3 - 1ºD/F, Coimbra, Coimbra, Portugal, +351936498277.

²School of Medicine and Biomedical Sciences, University of Porto, Porto, Portugal.

³2nd Division of Radiology, Medical University of Gdansk, Gdansk, Poland.

⁴Quantitative Imaging Biomarkers in Medicine, Quibim SL, Valencia, Spain.

⁵Research & Innovation, Nordic Healthcare Group, Espoo, Finland.

⁶Department of Oncology and Pathology, Karolinska Institutet, Solna, Sweden.

⁷Biomedical Imaging Research Group (GIBI230), La Fe Health Research Institute, Valencia, Spain.

⁸Department for Diagnostic and Interventional Radiology, University Hospital Dubrava, University of Zagreb School of Medicine, Zagreb, Croatia.

⁹Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain.

¹⁰R&D department (Health sector), Maggioli S.p.A - Greek branch, Marousi, Greece.

¹¹RISE-Health, Competences Centre on Active and Healthy Ageing (Porto4Ageing), Faculty of Pharmacy of University of Porto, Porto, Portugal.

PubMed PMC DOI PDF

Abstract

BACKGROUND: The successful design and implementation of artificial intelligence (AI)-driven solutions in health care requires early and continuous multidisciplinary and multiprofessional collaboration. However, diverse disciplinary educational backgrounds, varying languages, and cultural or geographic differences can lead to misunderstandings. To bridge this gap, a structured approach to AI requir…

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