Vol. 4 No. 1 (2024): Advances in Deep Learning Techniques
Articles

Data-Driven Dental Public Health: Improving Community Oral Health through Analytics

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  • Aneesh Reddy Pappireddy
Aneesh Reddy Pappireddy
Master Student, Health Data Science, Saint Louis University, Missouri, USA
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Published 10-05-2024

Keywords

  • Data-driven,
  • Dental public health,
  • Analytics,
  • Population-level data,
  • Disparities,
  • Interventions,
  • Resource allocation,
  • Machine learning,
  • Predictive modeling,
  • Oral health equity
    • ...More
    Less

How to Cite

[1]
A. Reddy Pappireddy, “Data-Driven Dental Public Health: Improving Community Oral Health through Analytics”, Adv. in Deep Learning Techniques, vol. 4, no. 1, pp. 67–79, May 2024.
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Abstract

Data-driven approaches are revolutionizing public health interventions, and dental public health is no exception. This paper explores the pivotal role of data analytics in enhancing community oral health outcomes. By harnessing population-level data, disparities in oral health can be identified, interventions can be targeted effectively, and resource allocation can be optimized. Through the integration of advanced analytics techniques, including machine learning and predictive modeling, dental public health practitioners can gain deeper insights into the factors influencing oral health outcomes within communities. This abstract provides an overview of the key components of data-driven dental public health, including data collection methods, analysis techniques, intervention strategies, and challenges faced. By leveraging the power of data analytics, dental public health initiatives can achieve greater precision, efficiency, and effectiveness in promoting oral health equity and improving overall community well-being.

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