Streamlining social media information retrieval for public health research with deep learning.

Journal: Journal of the American Medical Informatics Association : JAMIA
PMID: 38718216

Abstract

OBJECTIVE: Social media-based public health research is crucial for epidemic surveillance, but most studies identify relevant corpora with keyword-matching. This study develops a system to streamline the process of curating colloquial medical dictionaries. We demonstrate the pipeline by curating a Unified Medical Language System (UMLS)-colloquial symptom dictionary from COVID-19-related tweets as proof of concept.

Authors

  • Yining Hua
    Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Jiageng Wu
    School of Public Health, Zhejiang University School of Medicine, Zhejiang, China.
  • Shixu Lin
    School of Public Health, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310058, China.
  • Minghui Li
    MOE Key Laboratory of Geriatric Diseases and Immunology, School of Biology and Basic Medical Sciences, Suzhou Medical College of Soochow University, Suzhou, Jiangsu Province 215123, China.
  • Yujie Zhang
    Beijing University of Chinese Medicine, Beijing, 100029, China. zhyj227@126.com.
  • Dinah Foer
    Division of General Internal Medicine, Brigham and Women's Hospital, Boston, MA, USA; Division of Allergy and Clinical Immunology, Brigham and Women's Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA.
  • Siwen Wang
    College of Science, Huazhong Agricultural University, Wuhan 430070, P.R. China.
  • Peilin Zhou
    Thrust of Data Science and Analytics, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, Guangdong, 511458, China.
  • Jie Yang
    Key Laboratory of Development and Maternal and Child Diseases of Sichuan Province, Department of Pediatrics, Sichuan University, Chengdu, China.
  • Li Zhou
    School of Education, China West Normal University, Nanchong, Sichuan, China.

Keywords

External Resources

Popular Topics
Recent Journals