OralCam: Enabling Self-Examination and Awareness of Oral Health Using a Smartphone Camera
Yuan Liang, Hsuan-Wei Fan, Zhujun Fang, Leiying Miao, Wen Li, Xuan, Zhang, Weibin Sun, Kun Wang, Lei He, Xiang Anthony Chen

TL;DR
OralCam is a novel smartphone app that enables users to self-examine common oral conditions through photos, providing understandable results to promote oral health awareness, supported by expert validation and user studies.
Contribution
This work introduces the first interactive mobile app for self-examination of oral health conditions using deep learning and user-friendly explanations.
Findings
Achieved an average detection sensitivity of 0.787 for five oral conditions.
Most users found OralCam easy to use and interpret.
Expert validation supports OralCam's potential for oral health awareness.
Abstract
Due to a lack of medical resources or oral health awareness, oral diseases are often left unexamined and untreated, affecting a large population worldwide. With the advent of low-cost, sensor-equipped smartphones, mobile apps offer a promising possibility for promoting oral health. However, to the best of our knowledge, no mobile health (mHealth) solutions can directly support a user to self-examine their oral health condition. This paper presents OralCam, the first interactive app that enables end-users' self-examination of five common oral conditions (diseases or early disease signals) by taking smartphone photos of one's oral cavity. OralCam allows a user to annotate additional information (e.g. living habits, pain, and bleeding) to augment the input image, and presents the output hierarchically, probabilistically and with visual explanations to help a laymen user understand…
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Taxonomy
TopicsDental Research and COVID-19 · COVID-19 diagnosis using AI · Oral microbiology and periodontitis research
