jackleejm/rag-medication-ner repository overview

⁠General Information

This project demonstrates a novel application of Retrieval-Augmented Generation (RAG) for Named Entity Recognition (NER) in healthcare. The solution combines advanced search techniques and large language models (LLMs) to accurately extract medication-related entities, including drug names, dosages, quantities, administration types, and brands, from unstructured text. By leveraging hybrid search and reranking, the system achieves state-of-the-art accuracy in processing complex medical datasets.

For more information, do refer to the GitHub repository⁠ for more details.

Check out the accompanying article⁠ for more in-depth details on how and why this project was developed.