Deep Learning in Biomedicine - Challenges and Opportunities

Deep Learning in Biomedicine - Challenges and Opportunities

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Lessons learned

23 of 29

23 of 29

Lessons learned

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Deep Learning in Biomedicine - Challenges and Opportunities

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  1. 1 Intro
  2. 2 Precisions medicine
  3. 3 Big data vs. data science
  4. 4 Precision medicine
  5. 5 Biomedical data
  6. 6 Fast technological development
  7. 7 The Cancer Genome Atlas (TCGA)
  8. 8 Digital pathology
  9. 9 Biomedical images
  10. 10 Medical imaging
  11. 11 Introduction: Radiomics
  12. 12 Introduction: Traditional Radiomics
  13. 13 Semantic Features: Edge shape
  14. 14 Computational Features: Overview
  15. 15 Stanford Data Set
  16. 16 Decision tree modeling
  17. 17 Classifier: Decision trees
  18. 18 Introduction: Deep learning
  19. 19 Deep learning for medicine
  20. 20 Convolutional Neural Network
  21. 21 Melanoma diagnosis
  22. 22 Different types of images
  23. 23 Lessons learned
  24. 24 Background and Motivation
  25. 25 Conventional Approach
  26. 26 Brain Tumor Segmentation (Brats) Challenge
  27. 27 Ground truth
  28. 28 Visualizations
  29. 29 Overall summary

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