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Federated Learning for multi-center AI research in Dentistry (FLAID)

The primary objective of this multicenter research project is to harness the power of federated learning to enhance the development of diagnostic AI tools for dental imaging. By bringing together dental institutions and associated researchers, we aim to create a collaborative ecosystem that advances the accuracy, efficiency, and accessibility of dental radiographic diagnoses. Specifically, our project aims to:

1.                         Develop a federated learning framework for dental radiography that allows multiple institutions to collaboratively train AI models without sharing sensitive patient data.

2.                         Design and optimize AI algorithms for the automatic detection, classification and segmentation of dental anatomy and pathology.

3.                         Evaluate the performance of federated learning models against centralized models.