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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Online Access: | |
Physical Description: | 1 online resource (130 pages) |
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Table of 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.