# OralCam: Enabling Self-Examination and Awareness of Oral Health Using a Smartphone Camera

arXiv: https://arxiv.org/abs/2001.05621 · HTML: https://mlsanity.com/paper/2001.05621/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Jan 2020.

## Built on by (most cited first, 3 of 3)

- [Modality-aware Mutual Learning for Multi-modal Medical Image Segmentation](https://mlsanity.com/paper/2107.09842/) (2021)
- [An End-to-end Entangled Segmentation and Classification Convolutional Neural Network for Periodontitis Stage Grading from Periapical Radiographic Images](https://mlsanity.com/paper/2109.13120/) (2021)
- [Mobile Imaging Solutions for Medical Diagnosis: Trends and Applications](https://mlsanity.com/paper/2609.24814/) (2026)

## Abstract (arXiv)

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 examination results. Developed on our in-house dataset that consists of 3,182 oral photos annotated by dental experts, our deep learning based framework achieved an average detection sensitivity of 0.787 over five conditions with high localization accuracy. In a week-long in-the-wild user study (N=18), most participants had no trouble using OralCam and interpreting the examination results. Two expert interviews further validate the feasibility of OralCam for promoting users' awareness of oral health.