Keeling, A. orcid.org/0000-0003-4598-3744 (2026) Artificial Intelligence and Digital Impressions: The Positives and the Pitfalls. Australian Dental Journal. ISSN: 0045-0421
Abstract
Digital impressions are now central to contemporary dental workflows, driven by advances in CAD/CAM manufacturing and intraoral scanning technologies. In parallel, rapid progress in artificial intelligence (AI)—particularly deep learning—has led to its widespread integration into digital impression systems. AI already provides tangible clinical benefits, including real-time artefact removal, improved scan stitching, and more efficient three-dimensional data acquisition. However, these same techniques introduce new risks, most notably the silent modification or completion of scan data in regions of low confidence. Such inferred geometry may appear anatomically plausible while no longer representing a faithful record of the patient. This article examines where AI currently enhances digital impression accuracy and efficiency, and where it may compromise clinical validity. By distinguishing between beneficial data filtering and potentially misleading data inference, the aim is to support clinicians in making informed decisions and maintaining appropriate scrutiny of AI-assisted digital impressions.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2026 The Author(s). Australian Dental Journal published by John Wiley & Sons Australia, Ltd on behalf of Australian Dental Association. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
| Dates: |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Dentistry (Leeds) > Restorative Dentistry (Leeds) |
| Date Deposited: | 08 Sep 2026 15:26 |
| Last Modified: | 08 Sep 2026 15:26 |
| Published Version: | https://onlinelibrary.wiley.com/doi/10.1111/adj.70... |
| Status: | Published online |
| Publisher: | Wiley |
| Identification Number: | 10.1111/adj.70067 |
| Related URLs: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:245138 |
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