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From Indicators to Insights: Diversity-Optimized for Medical Series-Text Decoding via LLMs
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Studies how to make LLMs decode medical time series paired with text, focusing on diversity-optimized data for medical series-text decoding.
Problem
Medical time-series analysis needs domain knowledge and clinical context; LLMs could help by combining raw signals with literature and guideline knowledge, but precise decoding of series-text is hard.
Approach
Diversity-optimized training for medical series-text decoding with LLMs, using indicators to produce insights from medical time series; details beyond the abstract are not available.
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