Doctoral: A smartphone-based decision support tool for the early detection of oral potentially malignant disorders

Oral potentially malignant disorders can be defined as mucosal lesions and conditions with an increased risk of malignant transformation. Oral potentially malignant disorders are a significant health burden, and they are often diagnosed late due to scant attention to routine dental practice and the...

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Veröffentlicht in:Digital health 2023-01, Vol.9, p.20552076231177141-20552076231177141
Hauptverfasser: Di Fede, Olga, Panzarella, Vera, Buttacavoli, Fortunato, La Mantia, Gaetano, Campisi, Giuseppina
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Sprache:eng
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Zusammenfassung:Oral potentially malignant disorders can be defined as mucosal lesions and conditions with an increased risk of malignant transformation. Oral potentially malignant disorders are a significant health burden, and they are often diagnosed late due to scant attention to routine dental practice and the low number of specialized oral medicine centres. This report summarizes the DoctOral experience, a research initiative, providing a free smartphone-based decision support tool for the general medical/dental practitioner; the tool is based on the clinical appearance of oral lesions. Captured, oral pictures can be immediately examined via interactive decision trees and constructed on the smartphone. Such decision trees are expressed in standard formats, and they are readily accessible for facilitating the completion of a hypothetical diagnostic path. Since October 2017 the DoctOral mobile app has been downloaded by 10K + users, achieving a score of 4.8 out of 5. DoctOral also supports an unfolding joint initiative, called DoctOralAI: this involves selecting reference images, with which to create an open-source model, and perform a Case-Based Reasoning method, both of which are combined with machine learning. The DoctOral mobile app has revolutionized oral pathology by providing dental students and professionals with an interactive platform for recognizing and diagnosing oral lesions.
ISSN:2055-2076
2055-2076
DOI:10.1177/20552076231177141