Predictive Analytics in Dental Health: Leveraging Data for Early Detection and Prevention
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Keywords:
Predictive analytics, Dental health, Early detection, Prevention, Risk factors, Oral diseases, Data analysis, Healthcare, Personalized interventions, Treatment optimizationAbstract
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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License Terms
Ownership and Licensing:
Authors of this research paper submitted to the Journal of Science & Technology retain the copyright of their work while granting the journal certain rights. Authors maintain ownership of the copyright and have granted the journal a right of first publication. Simultaneously, authors agreed to license their research papers under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License.
License Permissions:
Under the CC BY-NC-SA 4.0 License, others are permitted to share and adapt the work, as long as proper attribution is given to the authors and acknowledgement is made of the initial publication in the Journal of Science & Technology. This license allows for the broad dissemination and utilization of research papers.
Additional Distribution Arrangements:
Authors are free to enter into separate contractual arrangements for the non-exclusive distribution of the journal's published version of the work. This may include posting the work to institutional repositories, publishing it in journals or books, or other forms of dissemination. In such cases, authors are requested to acknowledge the initial publication of the work in the Journal of Science & Technology.
Online Posting:
Authors are encouraged to share their work online, including in institutional repositories, disciplinary repositories, or on their personal websites. This permission applies both prior to and during the submission process to the Journal of Science & Technology. Online sharing enhances the visibility and accessibility of the research papers.
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Authors are responsible for ensuring that their research papers do not infringe upon the copyright, privacy, or other rights of any third party. The Journal of Science & Technology and The Science Brigade Publishers disclaim any liability or responsibility for any copyright infringement or violation of third-party rights in the research papers.