End-to-End Pipeline Integrating Local Small Language Models and Machine Learning for Data Extraction and Stroke Outcome Prediction in Emergency Department
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Background: A substantial proportion of clinical data is stored in unstructured text, limiting its utility for evidence generation. Small language models (SLMs) can extract information but face hallucination risks and privacy concerns. Locally deployable SLMs ... ...
