Large language model-based multi-source integration pipeline for automated diagnostic classification and zero-shot prognoses for brain tumor

Large language model-based multi-source integration pipeline for automated diagnostic classification and zero-shot prognoses for brain tumor

Purpose: In this study, we use large language models (LLMs) to integrate information from multi-source medical reports to enhance the accuracy of automated diagnostic classification and prognosis for brain tumors. Materials and Methods: Brain MRI reports from a cohort of 426 brain tumor patients wer...

Full description

Saved in:
Bibliographic Details
Main Authors: Zhuoqi Ma, Lulu Bi, Paige Collins, Owen Leary, Maliha Imami, Zhusi Zhong, Shaolei Lu, Grayson Baird, Nikos Tapinos, Ugur Cetintemel, Harrison Bai, Jerrold Boxerman, Zhicheng Jiao
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2025-06-01
Series:Meta-Radiology
Subjects:
Multi-source report
Large language model
Brain tumor
Automatic diagnosis
Prognosis
Online Access:http://www.sciencedirect.com/science/article/pii/S2950162825000189
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://www.sciencedirect.com/science/article/pii/S2950162825000189

Similar Items