AI in Pediatric Dentistry: Automated Diagnosis Overview
Author Information
Author(s): Rajinikanth Suba B., Rajkumar Densingh Samuel Raj, Rajinikanth Akshay, Anandhapandian Ponsekar Abraham, J. Bhuvaneswarri
Primary Institution: Srilalithambigai Medical College and Hospital, DR MGR Educational and Research Institute, Chennai, India
Hypothesis
This review aims to raise awareness about the novel applications of artificial intelligence in the field of pediatric dentistry.
Conclusion
AI tools can significantly enhance the accuracy and efficiency of diagnoses in pediatric dentistry.
Supporting Evidence
- AI can analyze large datasets to improve diagnostic accuracy.
- Machine learning models can predict dental issues in children with high accuracy.
- AI tools can assist in early detection of dental caries and other dental conditions.
Takeaway
This study talks about how computers can help dentists figure out dental problems in kids faster and more accurately.
Methodology
The review included original research studies focusing on automated diagnosis in pediatric dentistry using AI, with database searches conducted in PubMed, Embase, and Scopus.
Potential Biases
Potential bias due to the exclusion of non-English studies and ongoing studies.
Limitations
The review is concise and does not cover all aspects of AI applications in pediatric dentistry.
Participant Demographics
Studies included children aged 2-15 years.
Digital Object Identifier (DOI)
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