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Reading Race
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Classroom Contents
Preserving Patient Safety as AI Transforms Clinical Care - Curt Langlotz, Stanford University
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- 1 Intro
- 2 Clinical example
- 3 Health AI industry
- 4 Augmentation
- 5 Intelligent devices
- 6 Data needs
- 7 Narrative reports
- 8 Transformer models
- 9 How they work
- 10 Knowledge graphs
- 11 Results
- 12 Bone Age
- 13 Study
- 14 Underdiagnosis bias
- 15 Ethical machine learning
- 16 Generalizability
- 17 Reliability
- 18 Algorithm performance
- 19 Heatmaps
- 20 Explainability
- 21 Reading Race
- 22 High Pass vs Low Pass
- 23 MR Physics
- 24 Thank you
- 25 Questions
- 26 Deep reinforcement learning
- 27 Ethnicity detection
- 28 Physics training
- 29 Data collection
- 30 Differential privacy
- 31 Synthetic data
- 32 Data sharing
