Affiliation:
1. Nanjing University China
2. Nanjing Agricultural University China
3. Yonsei University Republic of Korea
4. Nanjing University of Science and Technology China
Abstract
ABSTRACTDrug–Drug Interaction (DDI) may affect the activity and efficacy of drugs, potentially leading to diminished therapeutic effect or even serious side effects. Therefore, automatic recognition of drug entities and relations involved in DDI is of great significance for pharmaceutical and medical care. In this paper, we propose a generative DDI triplets extraction framework based on Large Language Models (LLMs). We comprehensively apply various training methods, such as In‐context learning, Instruction‐tuning, and Task‐tuning, to investigate the biomedical information extraction capabilities of GPT‐3, OPT, and LLaMA. We also introduce Low‐Rank Adaptation (LoRA) technology to significantly reduce trainable parameters. The proposed method achieves satisfactory results in DDI triplet extraction, and demonstrates strong generalization ability on similar corpus.
Subject
Library and Information Sciences,General Computer Science
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