NLP for computational insights into nutritional impacts on colorectal cancer care

Colorectal cancer (CRC) is one of the most prominent cancers globally, with its incidence rising among younger adults due to improved screening practices. However, existing algorithms for CRC prediction are frequently trained on datasets that primarily reflect older persons, thus limiting their usef...

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Bibliographic Details

Published in:	SLAS Technology
Main Authors:	Shengnan Gong, Xiaohong Jin, Yujie Guo, Jie Yu
Format:	Article
Language:	English
Published:	Elsevier 2025-06-01
Subjects:	Natural language processing (NLP) Colorectal cancer (CRC) Nutritional impact CRC prediction framework (NICRP-framework) Dietary Patterns Adaptive Tunicate Swarm Optimized Large Language Models (ATSO-LLM)
Online Access:	http://www.sciencedirect.com/science/article/pii/S2472630325000536