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Computeraided mammography
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Classroom Contents
Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead - Cynthia Rudin
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- 1 Introduction
- 2 Bad decisions
- 3 Definitions
- 4 Why
- 5 Article
- 6 Crossvalidation
- 7 Accuracy interpretability
- 8 Two types of machine learning problems
- 9 Critically ill patients
- 10 Two helps to be
- 11 Optimization problem
- 12 Saliency maps
- 13 Casebased reasoning
- 14 My network
- 15 Prototype layer
- 16 Redbellied woodpecker
- 17 Wilsons warbler
- 18 Accuracy vs interpretability
- 19 Computeraided mammography
- 20 Interpretable AI
- 21 Case Study
- 22 Results
- 23 Two Layer Additive Risk Model
- 24 Submission to Special Issue
- 25 Paper
- 26 Problems
- 27 Most powerful argument
- 28 Papers
- 29 Interactive tool
- 30 Demo
- 31 Optimization
- 32 Machine Learning in Medicine
