LLM-MINE framework extracts Alzheimer's phenotypes from clinical notes

Researchers have developed LLM-MINE, a framework utilizing large language models to extract phenotypes related to Alzheimer's Disease and Related Dementias (ADRD) from clinical notes. This method aims to improve early detection and disease staging by analyzing unstructured text in electronic health records. The LLM-MINE framework, particularly when using few-shot prompting with combined phenotype lists, demonstrated superior performance in identifying statistically significant phenotype differences and in unsupervised disease staging compared to traditional biomedical NER and dictionary-based approaches. AI

IMPACT This research demonstrates the potential of LLMs to uncover clinically meaningful signals from unstructured medical data, potentially improving disease diagnosis and staging.

RANK_REASON The cluster contains an academic paper detailing a new framework for phenotype extraction using LLMs. [lever_c_demoted from research: ic=1 ai=1.0]

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• electronic health records
• Large Language Model
• LLM-MINE
• Mingchen Shao

• paper
• other

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