Designing with Machine Learning in Digital Pathology: Augmenting Medical Specialists through Interaction Design

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Lindvall, MartinLinköpings universitet,Medie- och Informationsteknik,Tekniska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV (författare)

Designing with Machine Learning in Digital Pathology : Augmenting Medical Specialists through Interaction Design

BokEngelska2021

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Linköping :Linköping University Electronic Press,2021
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LIBRIS-ID:oai:DiVA.org:liu-176117
ISBN:9789179296049
https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176117URI
https://doi.org/10.3384/diss.diva-176117DOI

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Språk:engelska
Sammanfattning på:engelska

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Linköping Studies in Science and Technology. Dissertations,0345-7524 ;2157

Anmärkningar

Recent advancements in machine learning (ML) have led to a dramatic increase in AI capabilities for medical diagnostic tasks. Despite technical advances, developers of predictive AI models struggle to integrate their work into routine clinical workflows. Inefficient human-AI interactions, poor sociotechnical fit and a lack of interactive strategies for dealing with the imperfect nature of predictions are known factors contributing to this lack of adoption.User-centred design methods are typically aimed at discovering and realising desirable qualities in use, pragmatically oriented around finding solutions despite the limitations of material- and human resources. However, existing methods often rely on designers possessing knowledge of suitable interactive metaphors and idioms, as well as skills in evaluating ideas through low-fidelity prototyping and rapid iteration methods—all of which are challenged by the data-driven nature of machine learning and the unpredictable outputs from AI models.Using a constructive design research approach, my work explores how we might design systems with AI components that aid clinical decision-making in a human-centred and iterative fashion. Findings are derived from experiments and experiences from four exploratory projects conducted in collaboration with professional physicians, all aiming to probe this design space by producing novel interactive systems for or with ML components.Contributions include identifying practical and theoretical design challenges, suggesting novel interaction strategies for human-AI collaboration, framing ML competence for designers and presenting empirical descriptions of conducted design processes. Specifically, this compilation thesis contains three works that address effective human-machine teaching and two works that address the challenge of designing interactions that afford successful decision-making despite the uncertainty and imperfections inherent in machine predictions.Finally, two works directly address design-researchers working with ML, arguing for a systematic approach to increase the repertoire available for theoretical annotation and understanding of the properties of ML as a designerly material.

Ämnesord och genrebeteckningar

HUMANIORA Konst Design hsv//swe
HUMANITIES Arts Design hsv//eng
NATURVETENSKAP Data- och informationsvetenskap Människa-datorinteraktion hsv//swe
NATURAL SCIENCES Computer and Information Sciences Human Computer Interaction hsv//eng

Biuppslag (personer, institutioner, konferenser, titlar ...)

Löwgren, Jonas,1964-Linköpings universitet,Medie- och Informationsteknik,Tekniska fakulteten(Swepub:liu)jonlo66 (preses)
Lundström, Claes,1973-Linköpings universitet,Medie- och Informationsteknik,Tekniska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV(Swepub:liu)clalu03 (preses)
Treanor, Darren,1974-Linköpings universitet,Medicinska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Region Östergötland, Klinisk patologi(Swepub:liu)dartr72 (preses)
Holzinger, Andreas,Associate ProfessorMedical University Graz, Austria (opponent)
Linköpings universitetMedie- och Informationsteknik (creator_code:org_t)

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Av författaren/redakt...: Lindvall, Martin; Löwgren, Jonas, ...; Lundström, Claes ...; Treanor, Darren, ...; Holzinger, Andre ...

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