COVID-19 Vaccine Adverse Event Detection Based on Multi-Label Classification With Various Label Selection Strategies-Reference-Cited by-同舟云学术

COVID-19 Vaccine Adverse Event Detection Based on Multi-Label Classification With Various Label Selection Strategies

Published:2023-09 Issue:9 Volume:27 Page:4192-4203
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Chen Donghua¹^ORCID,Zhang Runtong²^ORCID

Affiliation:

1. Department of Artificial Intelligence, School of Information Technology and Management, University of International Business and Economics, Beijing, China

2. Department of Information Management, School of Economics and Management, Beijing Jiaotong University, Beijing, China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Scientific Research Laboratory of AI Technology and Applications

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/10242175/10175519.pdf?arnumber=10175519

Reference63 articles.

1. MedDRA. Pharm;mozzicato;Medicine,2009

2. Natural language processing with deep learning for medical adverse event detection from free-text medical narratives: A case study of detecting total hip replacement dislocation

3. Advanced Clinical Decision Support for Vaccine Adverse Event Detection and Reporting

5. An mRNA Vaccine against SARS-CoV-2 — Preliminary Report

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Fully Automatic Fine-Grained Grading of Lumbar Intervertebral Disc Degeneration Using Regional Feature Recalibration Network;IEEE Journal of Biomedical and Health Informatics;2024-05