Application of Topic Modeling on Artificial Intelligence Studies as a Foundation to Develop Ethical Guidelines in African American Dementia Caregiving.

Journal: Studies in health technology and informatics
PMID: 37387087

Abstract

We applied natural language processing and topic modeling to publicly available abstracts and titles of 263 papers in the scientific literature mentioning AI and demographics (corpus 1 before Covid-19, corpus 2 after Covid-19) extracted from the MEDLINE database. We found exponential growth of AI studies mentioning demographics since the pandemic (Before Covid-19: N= 40 vs. After Covid-19: N= 223) [forecast model equation: ln(Number of Records) = 250.543*ln(Year) + -1904.38, p = 0.0005229]. Topics related to diagnostic imaging, quality of life, Covid, psychology, and smartphone increased during the pandemic, while cancer-related topics decreased. The application of topic modeling to the scientific literature on AI and demographics provides a foundation for the next steps regarding developing guidelines for the ethical use of AI for African American dementia caregivers.

Authors

  • Sunmoo Yoon
    School of Nursing, Columbia University Medical Center, New York, NY, USA.
  • Peter Broadwell
    Center for Interdisciplinary Digital Research, Stanford University, USA.
  • Frederick F Sun
    General Medicine, Department of Medicine, Columbia University, New York, NY, USA.
  • Maria De Planell-Saguer
    General Medicine, Department of Medicine, Columbia University, New York, NY, USA.
  • Nicole Davis
    School of Nursing, Clemson University, Clemson, SC, USA.

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