Researchers at the University of São Paulo (USP) have developed an artificial intelligence system that can recognize teeth and detect possible cavities in dental X-rays. Developed in Ribeirão Preto, the tool is designed to support dentists in analyzing images, potentially making clinical assessments faster and more precise.
The technology was developed through a collaboration between USP computer scientists and dental specialists. Around 30 researchers from the InReDD group are involved in the project, focusing on developing digital technologies for dentistry.
AI Trained to Support Dental Diagnosis
The AI uses convolutional neural networks trained on thousands of specialist-reviewed dental X-rays. It is designed to support dentists in diagnosis and treatment planning, not replace them.
The technology starts with a large collection of dental X-ray images that have been analyzed and labeled by specialists. These images train the AI to link X-ray patterns with dental abnormalities.
The system relies on convolutional neural networks, a type of AI architecture specifically designed to process visual information. According to Alessandra Alaniz Macedo, the architecture is well suited to image-based applications like dental radiography.
During the training process, the AI compares its predictions with the assessments made by specialists. Whenever it identifies discrepancies, the model adjusts its parameters to reduce errors. By repeating this process, the system gradually becomes better at detecting abnormalities in dental images.
Building and Evaluating the AI System
Developing the technology, however, involves more than simply programming an algorithm. Researchers must also select and prepare the data, train the model, and evaluate its performance. These stages form an essential part of the scientific work carried out by the computer science team.
In everyday clinical practice, the researchers envision artificial intelligence serving as an additional resource alongside a dentist’s own analysis. The technology could help professionals detect dental problems and support the preparation of appropriate treatment plans.
The project’s potential applications also extend beyond X-ray analysis. The team says AI could assist with dental practice tasks such as scheduling, patient inquiries, and communication.
Despite the encouraging results, the researchers stress that the technology is not intended to replace dentists. One of the challenges is that some AI models can be difficult to interpret, making it unclear how they reach specific conclusions—a limitation often described as the “black box” problem.
Camila Tirapelli, a professor at the Faculty of Dentistry of Ribeirão Preto and co-coordinator of the project with Alessandra Macedo, points out that no artificial intelligence system is completely error-free. For this reason, dentists must remain responsible for interpreting the results and determining the appropriate clinical approach.
Data Quality Is Key to Reliable AI
The reliability of the system also depends heavily on the quality of the data used for training. Tirapelli explains that poorly selected or inaccurate data may cause the AI to reproduce mistakes contained in its training material. Close collaboration between healthcare specialists and computer scientists is therefore essential for developing dependable AI models.
For patients, these technologies could shorten the time required for certain evaluations and help improve diagnostic accuracy.AI could also help researchers analyze large numbers of dental X-rays to identify trends and support oral health studies.
The solutions developed by InReDD are aimed at a range of users, including dentists, radiologists, and researchers. While the results achieved so far are encouraging, the systems are still being refined before they can be introduced more broadly into clinical practice.
Collaboration Across USP Drives the Project
The project brings together two USP units in Ribeirão Preto and involves researchers, professors, and students at different stages of academic training. The team includes undergraduate, master’s, and doctoral students, as well as postgraduates, postdoctoral researchers, and faculty members from the participating fields.
The initiative is also supported by funding from the São Paulo Research Foundation (FAPESP). The project focuses on combining artificial intelligence with dentistry through a technique known as multimodal fusion, opening up new opportunities for applying computing technologies to oral health.
According to Alessandra Macedo, integrating multiple functions into a single platform is one of the project’s main strengths. The research has already produced scientific publications, dissertations, and theses, as well as a technological product whose software code has been registered with USP.
The researchers plan to continue improving the systems and broaden their potential applications through future studies. Their long-term vision is for artificial intelligence to become a complementary tool in dentistry, while dentists continue to make the final clinical decisions.
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