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cs.CL2025
Enhancing Pancreatic Cancer Staging with Large Language Models: The Role of Retrieval-Augmented Generation
Hisashi Johno, Yuki Johno, Akitomo Amakawa +9
Purpose: Retrieval-augmented generation (RAG) is a technology to enhance the functionality and reliability of large language models (LLMs) by retrieving relevant information from r…
cs.CL2024
Application of NotebookLM, a Large Language Model with Retrieval-Augmented Generation, for Lung Cancer Staging
Ryota Tozuka, Hisashi Johno, Akitomo Amakawa +5
Purpose: In radiology, large language models (LLMs), including ChatGPT, have recently gained attention, and their utility is being rapidly evaluated. However, concerns have emerged…