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Classroom Contents
Weakly-Supervised, Large-Scale Computational Pathology for Diagnosis and Prognosis - Max Lu
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- 1 Introduction
- 2 Welcome
- 3 Background
- 4 Example
- 5 General workflow
- 6 Can we train accurate diagnostic or problem prognostic models
- 7 The same label assumption
- 8 Multiple instance learning
- 9 Data efficiency
- 10 Recap
- 11 Framework
- 12 Segmentation
- 13 Embedding
- 14 Attention pooling
- 15 Summary
- 16 Benchmarks
- 17 Attention scores
- 18 Cell phone microscopy
- 19 Results
- 20 Summarize
- 21 Code
- 22 Prognosis
- 23 Primary origins of ceps
- 24 Study design
- 25 Classification
- 26 Heatmaps
- 27 Interactive demo
- 28 Attention heating map
- 29 Dummy tool
- 30 High certainty diagnosis
- 31 Differential diagnosis
- 32 Thank you
- 33 Which regions in the slide will contribute
- 34 Can the primary originate from one single primary
- 35 Is the morphology more nuanced
- 36 Clustering
- 37 Outro
