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MINI REVIEW article

Front. Oral. Health
Sec. Oral Health Promotion
Volume 5 - 2024 | doi: 10.3389/froh.2024.1408867
This article is part of the Research Topic Responsible Artificial Intelligence and Machine Learning Methods for Equity in Oral Health View all articles

Responsible Artificial Intelligence for Addressing Equity in Oral Healthcare

Provisionally accepted
Zaid Khoury Zaid Khoury 1Alexys Ferguson Alexys Ferguson 1Jeffrey Price Jeffrey Price 2Ahmed S. Sultan Ahmed S. Sultan 2*Rong Wang Rong Wang 3*
  • 1 Meharry Medical College, Nashville, Tennessee, United States
  • 2 University of Maryland School of Dentistry, Baltimore, Maryland, United States
  • 3 School of Dentistry, University of Missouri–Kansas City, Kansas City, Missouri, United States

The final, formatted version of the article will be published soon.

    Oral diseases pose a significant burden on global healthcare. While many oral conditions are preventable and manageable through regular dental office visits, a substantial portion of the population faces obstacles in accessing essential and affordable quality oral healthcare. In this mini review, we describe the issue of inequity and bias in oral healthcare and discuss various strategies to address these challenges, with an emphasis on the application of artificial intelligence (AI). Recent advances in AI technologies have led to significant performance improvements in oral healthcare. AI also holds tremendous potential for advancing equity in oral healthcare, yet its application must be approached with caution to prevent the exacerbation of inequities. The “black box” approaches of some advanced AI models raise uncertainty about their operations and decision-making processes. To this end, we discuss the use of interpretable and explainable AI techniques in enhancing transparency and trustworthiness. Those techniques, aimed at augmenting rather than replacing oral health practitioners’ judgment and skills, have the potential to achieve personalized dental and oral care that is unbiased, equitable, and transparent. Overall, achieving equity in oral healthcare through the responsible use of AI requires collective efforts from all stakeholders involved in the design, implementation, regulation, and utilization of AI systems. We use the United States as an example due to its uniquely diverse population, making it an excellent model for our discussion. However, the general and responsible AI strategies suggested in this article can be applied to address equity in oral healthcare on a global level.

    Keywords: artificial intelligence, Interpretable models, Explainable models, responsible models, Equity, Bias, Oral healthcare

    Received: 28 Mar 2024; Accepted: 05 Jul 2024.

    Copyright: © 2024 Khoury, Ferguson, Price, Sultan and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Ahmed S. Sultan, University of Maryland School of Dentistry, Baltimore, Maryland, United States
    Rong Wang, School of Dentistry, University of Missouri–Kansas City, Kansas City, 64108, Missouri, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.