Endodontic Underfill

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Review clinical trials related to Endodontic Underfill. Use filters to narrow results by trial status, phase, treatment, biological sex and sponsor.

Condition / disease
Location
Status: Not yet recruiting

No Code Artificial Intelligence to Detect Radiographic Features Associated With Unsatisfactory Endodontic Treatment

Developing neural network-based models for image analysis can be time-consuming, requiring dataset design and model training. No-code AI platforms allow users to annotate object features without coding. Corrective annotation, a "human-in-the-loop" approach, refines AI segmentations iteratively. Dentistry has seen success with no-code AI for segmenting dental restorations. This study aims to assess radiographic features related to root canal treatment quality using a "human-in-the-loop" approach.

Participants needed: 80
Trial details
Age: 20-40Biological sex: AllType: InterventionalSponsor: University of CopenhagenUpdated: Jun 25, 2024
Eligibility criteria

Having any previous AI-related experiences [+1]