46 citations · 51 across the 4 of their papers we have counts for
4 papers
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…
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…
Extension of the one-sample Kolmogorov-Smirnov test
Atsushi Komaba, Hisashi Johno, Kazunori Nakamoto
We propose here a new goodness-of-fit test, named the one-sample OVL-q test (q = 1, 2, . . .), which can be considered an extension of the one-sample Kolmogorov-Smirnov test (equiv…
A novel statistical approach for two-sample testing based on the overlap coefficient
Atsushi Komaba, Hisashi Johno, Kazunori Nakamoto
Here we propose a new nonparametric framework for two-sample testing, named as the OVL- (). This can be regarded as a natural extension of the Smirnov test, wh…