Predictive Analytics in Dental Health: Leveraging Data for Early Detection and Prevention

Authors

  • Aneesh Reddy Pappireddy Master Student, Health Data Science, Saint Louis University, Missouri, USA Author

Keywords:

Predictive analytics, Dental health, Early detection, Prevention, Risk factors, Oral diseases, Data analysis, Healthcare, Personalized interventions, Treatment optimization

Abstract

This paper delves into the application of predictive analytics in the realm of dental health, aiming to discern patterns, trends, and risk factors associated with oral diseases. Leveraging extensive datasets and advanced analytical techniques, predictive analytics emerges as a potent tool for early detection and preventive interventions in dental care. Through the integration of diverse data sources, including patient records, imaging studies, and demographic information, predictive models can forecast oral health outcomes with remarkable accuracy. By identifying individuals at heightened risk of developing oral conditions such as caries, periodontal disease, and oral cancer, healthcare providers can tailor personalized interventions and allocate resources efficiently. Furthermore, predictive analytics facilitates the optimization of treatment plans, enhancing patient outcomes and minimizing healthcare costs. This paper underscores the transformative potential of predictive analytics in revolutionizing dental care delivery, fostering a proactive approach towards oral health management.

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Published

15-04-2024

How to Cite

[1]
A. Reddy Pappireddy, “Predictive Analytics in Dental Health: Leveraging Data for Early Detection and Prevention”, J. Sci. Tech., vol. 5, no. 2, pp. 121–137, Apr. 2024, Accessed: Apr. 23, 2026. [Online]. Available: https://thesciencebrigade.org/jst/article/view/196