Published on in Vol 24, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28858, first published .
Harnessing Artificial Intelligence for Health Message Generation: The Folic Acid Message Engine

Harnessing Artificial Intelligence for Health Message Generation: The Folic Acid Message Engine

Harnessing Artificial Intelligence for Health Message Generation: The Folic Acid Message Engine

Authors of this article:

Ralf Schmälzle1 Author Orcid Image ;   Shelby Wilcox1 Author Orcid Image

Journals

  1. Braga D, Oliveira D, Rosário R, Novais P, Machado J. An Architecture Proposal for Noncommunicable Diseases Prevention. Procedia Computer Science 2023;220:820 View
  2. Lim S, Schmälzle R. Exploring the mechanisms of AI message generation: A chatbot development activity for students. Communication Teacher 2024;38(1):21 View
  3. Lim S, Schmälzle R. Artificial intelligence for health message generation: an empirical study using a large language model (LLM) and prompt engineering. Frontiers in Communication 2023;8 View
  4. Zhang H, Pan J, Jiang H, Xiong X, Huang L, Liu X, Wangzi W, Chen L. A study on the correlation between MTHFR and folic acid combined with trace elements for the prevention of fetal malformations in the first trimester of pregnancy. Medicine 2023;102(44):e35330 View
  5. Addo-Lartey A, Bonful H, Sefenu R, Abagre T, Asamoah A, Bandoh D, Awua A, Adu-Aryee N, Dedey F, Adanu R, Okuyemi K. Effectiveness of a culturally tailored text messaging program for promoting cervical cancer screening in accra, Ghana: a quasi-experimental trial. BMC Women's Health 2024;24(1) View
  6. Lim S, Schmälzle R. The effect of source disclosure on evaluation of AI-generated messages. Computers in Human Behavior: Artificial Humans 2024;2(1):100058 View
  7. Haltaufderheide J, Ranisch R. The ethics of ChatGPT in medicine and healthcare: a systematic review on Large Language Models (LLMs). npj Digital Medicine 2024;7(1) View