4 ms·
When you say prediction my discharge disposition do you mean extracting from the document a statement of what the discharge disposition was? Or do you mean base
by jerrygenser 4y ago
When you say prediction my discharge disposition do you mean extracting from the document a statement of what the discharge disposition was? Or do you mean based on m extracted clinical characteristics, predicting what it should be?
For extracting what it was if it's in the document, you can use the indexing approach described in the article. For predicting what it should be, you'd probably be better off using llm as an extraction mechanism and then using structured data models to classify discharge disposition
- pilotneko 4y agoThe latter, not the former. The former is extraction, not prediction. A lot of factors go into predicting the post-acute care route that results in the best outcome. You are correct that it would be possible to create features using an LLM, but that is a very difficult problem compared to simply treating the problem as a sequence classification.
- jerrygenser 4y agoAgreed that there are better approaches than LLm to solve this problem There are deep learning and sequence models that are focused on this task using extracted structured info. Wouldn't you be better off using llm or any extraction + linking model to identify medical concepts and then a model that only understands medical concepts in order to do predict the next medical concepts.
- lmeyerov 4y agoYou can do layered retrieval and summarization/embeddings to fit within the context bounds. Conceptually it's not far from what a clinician would do anyway. By switching from a naive one shot prompt with big context to interactive (multiple calls) and summaries, no need to retrain But yeah my money is on context windows getting bigger and frameworks smoothing out how to do the above automatically, So it feels like a point in time optimization right now That will be tech debt by the end of the year