BioPRO: Context-Infused Prompt Learning for Biomedical Entity Linking-Reference-Cited by-同舟云学术

BioPRO: Context-Infused Prompt Learning for Biomedical Entity Linking

Published:2024 Issue: Volume:32 Page:374-385
ISSN:2329-9290
Container-title:IEEE/ACM Transactions on Audio, Speech, and Language Processing
language:
Short-container-title:IEEE/ACM Trans. Audio Speech Lang. Process.

Author:

Zhu Tiantian¹^ORCID,Qin Yang¹^ORCID,Feng Ming²^ORCID,Chen Qingcai¹^ORCID,Hu Baotian¹^ORCID,Xiang Yang³^ORCID

Affiliation:

1. School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, China

2. Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

3. Peng Cheng Laboratory, Shenzhen, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Science and Technology Planning Project of Shenzhen

Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Acoustics and Ultrasonics,Computer Science (miscellaneous),Computational Mathematics

Link

http://xplorestaging.ieee.org/ielx7/6570655/10304349/10313039.pdf?arnumber=10313039

Reference66 articles.

1. Self-Alignment Pretraining for Biomedical Entity Representations

2. Calibrating variant-scoring methods for clinical decision making

3. CNN-based ranking for biomedical entity normalization

4. BioCreative V CDR task corpus: a resource for chemical disease relation extraction

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