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Formulate the inputs and outputs for an end-to-end medical QA system.
Case context: You are leading a machine learning team developing a system to help doctors find information quickly. The system must process medical documents and answer specific clinical questions.
Question: Based on the principles of end-to-end question answering in Machine Learning Yearning, decide what specific data structures your team must provide as input to the system and what exact format the system should generate as output.
Sample answer: The team must provide the system with a paired input consisting of the medical text (the document) and the specific clinical question being asked, functioning together as a (Text, Question) pair. The system should be designed to generate answer text as its output, which will directly address the clinical question based on the provided document.
Key points:
- Input must be a (Text, Question) pair.
- The text component represents the medical document.
- The question component represents the clinical query.
- Output must be the generated answer text.
Rubric: Award points if the learner correctly identifies the input as a combination of text and a question, and the output as the generated answer text.
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Machine Learning
Deep Learning
Supervised Learning
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Data Science
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Formulate the inputs and outputs for an end-to-end medical QA system.
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