Exploration of AI-Powered Tools for Risk Assessment in General Dentistry
Background: The integration of artificial intelligence (AI) in dentistry has transformed diagnostic accuracy and treatment planning. AI-powered tools have shown promise in enhancing risk assessment, enabling early identification of oral health conditions. Materials and Methods: A prospective study w...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wolters Kluwer Medknow Publications
2025-06-01
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| Series: | Journal of Pharmacy and Bioallied Sciences |
| Subjects: | |
| Online Access: | https://journals.lww.com/10.4103/jpbs.jpbs_83_25 |
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| Summary: | Background:
The integration of artificial intelligence (AI) in dentistry has transformed diagnostic accuracy and treatment planning. AI-powered tools have shown promise in enhancing risk assessment, enabling early identification of oral health conditions.
Materials and Methods:
A prospective study was conducted to evaluate the efficiency of an AI-powered risk assessment tool. A total of 150 patients, aged 18–65 years, were included in the study. Patients underwent standard clinical examinations, followed by AI-based risk assessment using a machine learning platform trained on a dataset of 10,000 cases. The tool analyzed factors, such as oral hygiene habits, dietary patterns, and medical history, to generate individualized risk scores. Statistical analysis compared AI-generated risk assessments with those of dental experts to measure accuracy and reliability.
Results:
The AI tool demonstrated a sensitivity of 91% and a specificity of 88% in identifying high-risk cases. Of the 150 patients, 45 were identified as high risk, 70 as moderate risk, and 35 as low risk by the AI tool. Expert evaluation aligned with AI predictions in 92% of cases, confirming the tool’s reliability. Time required for risk assessment was reduced by 40% compared to manual evaluations.
Conclusion:
AI-powered tools offer significant advantages in general dentistry by improving the accuracy and efficiency of risk assessment. These tools can serve as valuable adjuncts to clinical expertise, enabling early interventions and personalized care strategies. |
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| ISSN: | 0976-4879 0975-7406 |