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Diagnosing a Medical Imaging Algorithm using Doctor Intuitions
Case context: Your team has deployed a medical imaging algorithm to detect a specific abnormality. However, during testing, the algorithm performs worse than the team of human doctors on the task.
Question: According to Machine Learning Yearning, what is the recommended approach to diagnose and improve this algorithm using the doctors' expertise, and what exactly are you trying to extract from them?
Sample answer: The recommended approach is to discuss the specific misclassified images with the team of doctors to draw on their intuitions. The goal is to understand exactly what visual information or context the doctors are using to arrive at the correct diagnosis, so that this knowledge can be used to modify the learning algorithm to look for similar information.
Key points:
- Discuss images with a team of doctors
- Draw on doctors' intuitions
- Understand what information they use to get the correct answer
- Use the knowledge to modify the algorithm
Rubric: A good answer should mention discussing the images directly with doctors and the goal of extracting the specific information/intuitions they use to make correct decisions.
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Diagnosing a Medical Imaging Algorithm using Doctor Intuitions
Goal of Using Human Intuition in Error Analysis