Digital workflows and artificial intelligence driven diagnosis and treatment planning in orthodontics

Provisional description of the objective(s) of the doctoral dissertation (research plan), the methodology and timing: The content of this doctoral project: 1. A systematic review of the literature for digital work-flows and AI enhanced procedures in orthodontics. 2. Development and validation of an artificial intelligence-based tool for automated bone segmentation in the oral and maxillofacial region 3. Development and validation of an artificial intelligence-based tool for predicting volumetric biologic limitations for tooth movement in orthodontics. 4. Development and validation of an artificial intelligence-based tool for predicting biologic limitations related to maturation for maxillary orthopedics. 5. Development and validation of an artificial intelligence-based tool for temporary anchorage devices placement 6. Development and validation of an artificial intelligence-based tools for automated tooth segmentation on digital study models 7. Development and validation of an artificial intelligence-based tools for enhancing digital study models in preparation for indirect bonding 8. Clinical trial to test the accuracy of indirect bonding techniques based on AI driven planning. Timing: The research will be performed over a period of six years. A search of the literature, development of the research projects and ethical approval will be performed. Inclusion and exclusion criteria for both patients and imaging modalities will be established. For the AI enhanced tools the generated database will be fed to an AI algorithm. Results will be evaluated and training adjusted accordingly. A validation study for each AI-driven procedure/tool will be conducted. A clinical evaluation and a randomized clinical trial could further establish the benefits of using such techniques over conventional methods. Patient selection and segmentation of the different tissues will be ongoing during the whole duration of the doctoral program – allowing for refinement of the results and the accuracy of the algorithm. AI-driven segmentations of the different oral tissues included in the model should be validated by the third year, AI- planning tools should be validated towards the fourth year, to therefore be able to combine the different parts together and produce a complete statistical analysis and scientific articles during the fifth and six years.