Applications of Natural Language Processing and Large Language Models for Social Determinants of Health: Protocol for a Systematic Review.

Journal: JMIR research protocols
PMID: 39836952

Abstract

BACKGROUND: In recent years, the intersection of natural language processing (NLP) and public health has opened innovative pathways for investigating social determinants of health (SDOH) in textual datasets. Despite the promise of NLP in the SDOH domain, the literature is dispersed across various disciplines, and there is a need to consolidate existing knowledge, identify knowledge gaps in the literature, and inform future research directions in this emerging field.

Authors

  • Swati Rajwal
    Department of Computer Science and Informatics, Emory University, Atlanta, GA, United States.
  • Ziyuan Zhang
    Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States.
  • Yankai Chen
    School of Biomedical Engineering and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China.
  • Hannah Rogers
    Woodruff Health Sciences Center Library, Emory University, Atlanta, GA, United States.
  • Abeed Sarker
    Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, United States.
  • Yunyu Xiao
    Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.

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