Designing with Machine Learning in Digital Pathology : : Augmenting Medical Specialists Through Interaction Design.
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Superior document: | Linköping Studies in Science and Technology. Dissertations Series ; v.2157 |
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Place / Publishing House: | Linköping : : Linkopings Universitet,, 2021. {copy}2021. |
Year of Publication: | 2021 |
Edition: | 1st ed. |
Language: | English |
Series: | Linköping Studies in Science and Technology. Dissertations Series
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Physical Description: | 1 online resource (130 pages) |
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Lindvall, Martin. Designing with Machine Learning in Digital Pathology : Augmenting Medical Specialists Through Interaction Design. 1st ed. Linköping : Linkopings Universitet, 2021. {copy}2021. 1 online resource (130 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier Linköping Studies in Science and Technology. Dissertations Series ; v.2157 Intro -- Abstract -- Acknowledgments -- List of Publications -- Contents -- I Comprehensive Summary -- 1 Introduction -- 1.1 Research Scope and Delimitations -- 1.2 Thesis Overview -- 2 Background -- 2.1 Machine Learning Basics -- 2.2 Digital Pathology -- 2.3 Artificial Intelligence in Pathology -- 3 Theoretical Framework -- 3.1 Automation and Human Control -- 3.2 Challenges Designing with ML -- 3.3 AI-assisted Decision-making -- 4 Research Approach -- 4.1 Constructive Design Research -- 4.2 Motivations -- 4.3 From Design Experiments to Generative Knowledge -- 4.4 Designing for Efficiency -- 5 Paper summary -- 6 Design Experiments -- 6.1 Overview -- 6.2 Exploring Proactive Training Data Collection (DROID) -- 6.3 AI-assisted Annotation (TW) -- 6.4 AI-assisted Visual Search (LGL) -- 6.5 AI-assisted Quantification (PDL1) -- 7 A Framework for Designing Human-Centred Machine Learning -- 7.1 The Importance of Thoughtful Action -- 7.2 Three Interconnected Activities -- 7.3 The Impact of Gathering Training Data -- 7.4 The Impact of Interaction Design -- 7.5 The Impact of Model Development -- 8 Conclusion and Discussion -- 8.1 Summary of Contributions -- 8.2 Why is Designing with ML Difficult? -- 8.3 Power to the People? Reflections on Interactive Machine Learning -- 8.4 The Role of Constructive Design Research -- 8.5 In Conclusion -- Bibliography -- II Appended papers -- 1 TissueWand, a Rapid Histopathology Annotation Tool. -- 2 Rapid Assisted Visual Search: Supporting Digital Pathologists with Imperfect AI. -- 3 From Machine Learning to Machine Teaching: The Importance of UX. -- 4 Machine Learning as a Design Material: a Curated Collection of Exemplars for Visual Interaction. -- 5 Verification Staircase: a Design Strategy for Actionable Explanations. -- 6 Designing for the Long-Tail of Machine Learning. 7 Proactive Construction of an Annotated Imaging Database for Artificial Intelligence Training. Description based on publisher supplied metadata and other sources. Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries. Electronic books. Print version: Lindvall, Martin Designing with Machine Learning in Digital Pathology Linköping : Linkopings Universitet,c2021 ProQuest (Firm) Linköping Studies in Science and Technology. Dissertations Series https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=6720003 Click to View |
language |
English |
format |
eBook |
author |
Lindvall, Martin. |
spellingShingle |
Lindvall, Martin. Designing with Machine Learning in Digital Pathology : Augmenting Medical Specialists Through Interaction Design. Linköping Studies in Science and Technology. Dissertations Series ; Intro -- Abstract -- Acknowledgments -- List of Publications -- Contents -- I Comprehensive Summary -- 1 Introduction -- 1.1 Research Scope and Delimitations -- 1.2 Thesis Overview -- 2 Background -- 2.1 Machine Learning Basics -- 2.2 Digital Pathology -- 2.3 Artificial Intelligence in Pathology -- 3 Theoretical Framework -- 3.1 Automation and Human Control -- 3.2 Challenges Designing with ML -- 3.3 AI-assisted Decision-making -- 4 Research Approach -- 4.1 Constructive Design Research -- 4.2 Motivations -- 4.3 From Design Experiments to Generative Knowledge -- 4.4 Designing for Efficiency -- 5 Paper summary -- 6 Design Experiments -- 6.1 Overview -- 6.2 Exploring Proactive Training Data Collection (DROID) -- 6.3 AI-assisted Annotation (TW) -- 6.4 AI-assisted Visual Search (LGL) -- 6.5 AI-assisted Quantification (PDL1) -- 7 A Framework for Designing Human-Centred Machine Learning -- 7.1 The Importance of Thoughtful Action -- 7.2 Three Interconnected Activities -- 7.3 The Impact of Gathering Training Data -- 7.4 The Impact of Interaction Design -- 7.5 The Impact of Model Development -- 8 Conclusion and Discussion -- 8.1 Summary of Contributions -- 8.2 Why is Designing with ML Difficult? -- 8.3 Power to the People? Reflections on Interactive Machine Learning -- 8.4 The Role of Constructive Design Research -- 8.5 In Conclusion -- Bibliography -- II Appended papers -- 1 TissueWand, a Rapid Histopathology Annotation Tool. -- 2 Rapid Assisted Visual Search: Supporting Digital Pathologists with Imperfect AI. -- 3 From Machine Learning to Machine Teaching: The Importance of UX. -- 4 Machine Learning as a Design Material: a Curated Collection of Exemplars for Visual Interaction. -- 5 Verification Staircase: a Design Strategy for Actionable Explanations. -- 6 Designing for the Long-Tail of Machine Learning. 7 Proactive Construction of an Annotated Imaging Database for Artificial Intelligence Training. |
author_facet |
Lindvall, Martin. |
author_variant |
m l ml |
author_sort |
Lindvall, Martin. |
title |
Designing with Machine Learning in Digital Pathology : Augmenting Medical Specialists Through Interaction Design. |
title_sub |
Augmenting Medical Specialists Through Interaction Design. |
title_full |
Designing with Machine Learning in Digital Pathology : Augmenting Medical Specialists Through Interaction Design. |
title_fullStr |
Designing with Machine Learning in Digital Pathology : Augmenting Medical Specialists Through Interaction Design. |
title_full_unstemmed |
Designing with Machine Learning in Digital Pathology : Augmenting Medical Specialists Through Interaction Design. |
title_auth |
Designing with Machine Learning in Digital Pathology : Augmenting Medical Specialists Through Interaction Design. |
title_new |
Designing with Machine Learning in Digital Pathology : |
title_sort |
designing with machine learning in digital pathology : augmenting medical specialists through interaction design. |
series |
Linköping Studies in Science and Technology. Dissertations Series ; |
series2 |
Linköping Studies in Science and Technology. Dissertations Series ; |
publisher |
Linkopings Universitet, |
publishDate |
2021 |
physical |
1 online resource (130 pages) |
edition |
1st ed. |
contents |
Intro -- Abstract -- Acknowledgments -- List of Publications -- Contents -- I Comprehensive Summary -- 1 Introduction -- 1.1 Research Scope and Delimitations -- 1.2 Thesis Overview -- 2 Background -- 2.1 Machine Learning Basics -- 2.2 Digital Pathology -- 2.3 Artificial Intelligence in Pathology -- 3 Theoretical Framework -- 3.1 Automation and Human Control -- 3.2 Challenges Designing with ML -- 3.3 AI-assisted Decision-making -- 4 Research Approach -- 4.1 Constructive Design Research -- 4.2 Motivations -- 4.3 From Design Experiments to Generative Knowledge -- 4.4 Designing for Efficiency -- 5 Paper summary -- 6 Design Experiments -- 6.1 Overview -- 6.2 Exploring Proactive Training Data Collection (DROID) -- 6.3 AI-assisted Annotation (TW) -- 6.4 AI-assisted Visual Search (LGL) -- 6.5 AI-assisted Quantification (PDL1) -- 7 A Framework for Designing Human-Centred Machine Learning -- 7.1 The Importance of Thoughtful Action -- 7.2 Three Interconnected Activities -- 7.3 The Impact of Gathering Training Data -- 7.4 The Impact of Interaction Design -- 7.5 The Impact of Model Development -- 8 Conclusion and Discussion -- 8.1 Summary of Contributions -- 8.2 Why is Designing with ML Difficult? -- 8.3 Power to the People? Reflections on Interactive Machine Learning -- 8.4 The Role of Constructive Design Research -- 8.5 In Conclusion -- Bibliography -- II Appended papers -- 1 TissueWand, a Rapid Histopathology Annotation Tool. -- 2 Rapid Assisted Visual Search: Supporting Digital Pathologists with Imperfect AI. -- 3 From Machine Learning to Machine Teaching: The Importance of UX. -- 4 Machine Learning as a Design Material: a Curated Collection of Exemplars for Visual Interaction. -- 5 Verification Staircase: a Design Strategy for Actionable Explanations. -- 6 Designing for the Long-Tail of Machine Learning. 7 Proactive Construction of an Annotated Imaging Database for Artificial Intelligence Training. |
isbn |
9789179296049 |
genre |
Electronic books. |
genre_facet |
Electronic books. |
url |
https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=6720003 |
illustrated |
Not Illustrated |
oclc_num |
1267762249 |
work_keys_str_mv |
AT lindvallmartin designingwithmachinelearningindigitalpathologyaugmentingmedicalspecialiststhroughinteractiondesign |
status_str |
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ids_txt_mv |
(MiAaPQ)5006720003 (Au-PeEL)EBL6720003 (OCoLC)1267762249 |
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hierarchy_parent_title |
Linköping Studies in Science and Technology. Dissertations Series ; v.2157 |
is_hierarchy_title |
Designing with Machine Learning in Digital Pathology : Augmenting Medical Specialists Through Interaction Design. |
container_title |
Linköping Studies in Science and Technology. Dissertations Series ; v.2157 |
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