IDEAS home Printed from https://ideas.repec.org/a/plo/pdig00/0000938.html
   My bibliography  Save this article

The role of artificial intelligence in maternal and child health: Progress, controversies, and future directions

Author

Listed:
  • Audêncio Victor

Abstract

This debate paper examines the transformative potential of Artificial Intelligence (AI), specifically through Machine Learning (ML), in enhancing preventive measures in maternal and child health (MCH). With the proliferation of Big Data, ML has become crucial in handling complex, non-linear interactions among health determinants to not only predict but also prevent adverse outcomes. This paper underscores AI’s applications in early interventions that could decrease the incidence of MCH issues. It reviews technological advancements while addressing ethical, practical, and data-related challenges in applying AI in preventive healthcare. Emphasis is placed on recent supervised, unsupervised, and reinforcement learning applications that significantly advance preventive care, particularly in low-resource settings. The manuscript discusses the development of AI models for early diagnosis, comprehensive risk assessments, and customized preventive interventions, while highlighting challenges like data diversity, privacy issues, and integrating multimodal health data.

Suggested Citation

  • Audêncio Victor, 2025. "The role of artificial intelligence in maternal and child health: Progress, controversies, and future directions," PLOS Digital Health, Public Library of Science, vol. 4(7), pages 1-8, July.
  • Handle: RePEc:plo:pdig00:0000938
    DOI: 10.1371/journal.pdig.0000938
    as

    Download full text from publisher

    File URL: https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000938
    Download Restriction: no

    File URL: https://journals.plos.org/digitalhealth/article/file?id=10.1371/journal.pdig.0000938&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pdig.0000938?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pdig00:0000938. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: digitalhealth (email available below). General contact details of provider: https://journals.plos.org/digitalhealth .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.