Large Language Model–Enhanced Drug Repositioning Knowledge Extraction via Long Chain-of-Thought: Development and Evaluation Study

LCoDR-KE enhances LLMs' domain-specific adaptability for drug repositioning by offering an open-source drug repositioning corpus and a long chain-of-thought framework based on a lightweight LLM model. This framework supports drug discovery and knowledge reasoning while providing scalable, interpretable solutions applicable to broader biomedical knowledge extraction tasks.

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Publication Details

Journal
JMIR Medical Informatics
Published
2025-09-03
DOI
https://doi.org/10.2196/77837
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
0.00
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article

Large Language Model–Enhanced Drug Repositioning Knowledge Extraction via Long Chain-of-Thought: Development and Evaluation Study

Hongyu Kang, Si Zheng, Xiaowei Xu, Jiao Li et al.
JMIR Medical Informatics
Topic Modeling
article

Large Language Model–Enhanced Drug Repositioning Knowledge Extraction via Long Chain-of-Thought: Development and Evaluation Study

Hongyu Kang, Si Zheng, Xiaowei Xu, Jiao Li, Li Hou, Qin Li
article en

Abstract

LCoDR-KE enhances LLMs' domain-specific adaptability for drug repositioning by offering an open-source drug repositioning corpus and a long chain-of-thought framework based on a lightweight LLM model. This framework supports drug discovery and knowledge reasoning while providing scalable, interpretable solutions applicable to broader biomedical knowledge extraction tasks.

JMIR Medical InformaticsVol. 13
Beijing Institute of Technology (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
Openalex Percentile: Top 88%
Topic Modeling
DOIOpen Access PDFOpenAlex
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Large Language Model–Enhanced Drug Repositioning Knowledge Extraction via Long Chain-of-Thought: Development and Evaluation Study — Hongyu Kang, Si Zheng, et al. · JMIR Medical Informatics (2025) | TGRS Research Map | TGRS