@article{10.37349/edht.2025.101138,
abstract = {Confocal laser endomicroscopy (CLE) enables real-time diagnosis of oral cancer and potentially malignant disorders by in vivo microscopic tissue examination. One impediment to the widespread clinical adoption of this technology is the need for operator expertise in image interpretation. Here we review the application of AI to automatic tissue classification of CLE images and discuss the opportunities for integrating this technology to advance the adoption of real-time digital pathology thus improving speed, precision and reproducibility.},
author = {Fox, Simon A. and Farah, Camile S.},
doi = {10.37349/edht.2025.101138},
journal = {Exploration of Digital Health Technologies},
elocation-id = {101138},
title = {Artificial intelligence driven real-time digital oral microscopy for early detection of oral cancer and potentially malignant disorders},
url = {https://www.explorationpub.com/Journals/edht/Article/101138},
volume = {3},
year = {2025}
}