Artificial intelligence strategies based on random forests for detection of AI-generated content in public health.

Journal: Public health
PMID: 40188709

Abstract

OBJECTIVES: To train and test a Random Forest machine learning model with the ability to distinguish AI-generated from human-generated textual content in the domain of public health, and public health policy.

Authors

  • Igor V Pantic
    University of Belgrade, Faculty of Medicine, Dr. Subotića 8, 11129, RS-11129, Belgrade, Serbia; University of Haifa, 199 Abba Hushi Blvd, Mount Carmel, Haifa, IL-3498838, Israel; Ben-Gurion University of the Negev, Faculty of Health Sciences, 84105, Be'er Sheva, Israel. Electronic address: igor.pantic@med.bg.ac.rs.
  • Snezana Mugosa
    University of Montenegro, Faculty of Medicine, Kruševac bb, 81000, Podgorica, Montenegro; Institute for Medicine and Medical Devices of Montenegro, Blvd. Ivana Crnojevića 64a, Podgorica, Montenegro.

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