This narrative review aims to appraise the evidence on artificial intelligence models for early diagnosis and risk stratification of oral cancer, focusing on data modalities, methodology differences, applications in the diagnostic flow and models’ performance. Models for early diagnosis and screening provide non-invasive diagnosis without the need for specialized instruments, which is ideal for early detection as a low-cost system. Supervised learning with well-annotated data provides reliable references for training the models, and therefore, reliable and promising results. Risk prediction models can be built based on medical record data, demographic data, clinical/histopathological descriptors, highly standardized images or a combination of these. Insights on which patients have a greater chance of malignancy development or disease recurrence can aid in providing personalized care, which can improve the patient’s prognosis. Artificial intelligence models demonstrate promising results in early diagnosis and risk stratification of oral cancer.

This study aims to assess a new mobile application (app)’s efficacy in raising oral cancer awareness among older adults through educational videos and serious games. The app, named TEGO^® (Tele-platform of Geriatric and Dental Specialties), with a video about oral cancer prevention, oral-self-examination, and serious gaming elements, like trivia and word search puzzles to reinforce the acquired knowledge was developed. Fifty-six patients, aged 60 to 80 years, were randomly selected from the Dental Clinic of the University of Chile and invited to use the app on their personal smartphones. Knowledge and attitudes were evaluated before two and four weeks after use. Oral self-examination practices were measured with a checkup guideline. The participation rate was 41.1%, mostly male (52.2%). Before using the app, 30.4% of the participants reported awareness of oral cancer, and none had performed oral self-examinations. Following two weeks after use, there was notable engagement, with 100% of participants utilizing it and responding that they had heard about oral cancer, and 56.5% having practiced an oral self-examination. This last outcome increased to 82.6% in the fourth week. The use of mHealth technologies has the potential as an effective educational tool for disseminating knowledge about oral cancer among older adults.

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.

Teledentistry has emerged as a promising tool in bridging the gap in healthcare accessibility, particularly in regions like Latin America region, where resources for oral healthcare are often limited. Drawing upon a comprehensive review of literature, this overview assessed the applications and clinical outcomes of teledentistry in diagnosing oral potentially malignant disorders (OPMDs) and oral cancer, highlighting the challenges and opportunities specific to the Latin American context. Moreover, it examined the integration of artificial intelligence algorithms and teledentistry for enhancing diagnostic accuracy, thereby optimizing resource allocation and improving patient outcomes. By elucidating the current landscape and future prospects, this overview provided insights for policymakers, healthcare providers, and researchers, fostering advancements in oral healthcare delivery with the aim of reducing the burden of OPMDs and oral cancer in the Latin American region.

Geographic areas like Argentine Patagonia face significant barriers in the fight against oral cancer due to great distances, extreme weather conditions, and a shortage of specialists. These factors contribute to delayed diagnosis and treatment, adversely affecting patient outcomes. The aim of this study was to describe a pilot project to establish the telemedicine network of Chubut (Argentine Patagonia) for the early diagnosis of oral cancer. This perspective study also aimed to describe the advantages and disadvantages of using this tool in remote areas with limited access to healthcare services. Healthcare professionals, including nurses, dentists, doctors, and healthcare workers, were trained in the early diagnosis of oral cancer and high-risk oral lesions by five specialists in Oral Medicine, who traveled throughout Argentine Patagonia. Additionally, training was provided on the use of smartphones to obtain clinical images and data for remote consultations via telemedicine with a specialized center. Over 2,000 km were traveled, and more than 100 healthcare professionals were trained in six towns and localities in Patagonia, Argentina, encountering various limitations for the use of telemedicine in remote areas, such as connectivity issues. The first telemedicine network of Patagonia for the diagnosis of oral cancer was created and is now operational, receiving teleconsultations and referrals from the professionals trained during the journey. This study highlighted that telemedicine is an important tool to overcome geographical barriers and improve access to medical care, especially in remote areas. It promotes agility and speed in referrals and optimizes the available resources of the health system. Future studies should analyze the impact of telemedicine in decreasing the delay of oral cancer diagnosis in Southern Argentina.

In the United Kingdom (UK), the current prevalence rates of oropharyngeal cancer linked to human papillomavirus (HPV) are 6.29% and 2.04% in men and women, respectively. Over the years, the burden of this disease has increased in the UK, and this is mainly due to the rising prevalence of HPV infection in the UK. Research evidence has shown that over 70% of oropharyngeal cancers in the UK are linked to HPV. Oral sex is the major route of transmission of HPV, and over 63% of UK young adults are found to have a positive history of oral sex practice. However, only a minority of the UK population are aware of HPV-associated oropharyngeal cancer; this therefore calls for more public health efforts to increase awareness and knowledge on HPV-associated oropharyngeal cancer in the UK. While the use of technology-based, clinic-based, and community-based interventions have been employed to improve public awareness and knowledge on the role of HPV-associated oropharyngeal cancer, mobile health (mhealth) interventions have not been seriously explored despite existing robust evidence on the effective roles of mhealth in improving awareness and knowledge in diverse diseases. This article therefore calls for the adoption and use of mhealth interventions in educating the UK’s population on HPV-associated oropharyngeal cancer. The use of mhealth interventions in this regard is highly viable as its implementation closely aligns with the country’s National Health Service (NHS) commitment towards the digital transformation of the UK’s healthcare system.

Photographic images are an essential tool in oral medicine practice, even though their value is conditioned by their quality. Digital photography using smartphones (SPhs) has had many advances, nowadays allowing the acquisition of high-quality pictures. Compared to professional cameras, it has advantages and disadvantages. The latter comprise photographs out of focus, poorly framed, and lighting problems due to shadows, artifacts, and color alterations, among other problems mainly mediated by the operator. Such defects can limit the proper interpretation of the image representing the patient’s condition. This perspective aims to describe the basic concepts of photography and the functional features of SPhs. This will allow programming those devices properly for oral telemedicine (OTM), understanding their limitations, and correcting errors for the photographs to be used effectively. We also include empirical solutions and illustrations showing that photography with SPhs could be easily executable by any health professional and even by the patients themselves.

Epithelial dysplasia is a condition characterized by a spectrum of architectural and cytological alterations to the epithelium, resulting from the accumulation of genetic alterations. It is associated with an increased risk of cancer progression in a variety of organs. However, the variability of different grading systems, as well as inter- and intra-examiner variability, gives rise to concerns regarding the reliability of the results. Histopathology represents the gold standard for the diagnosis of epithelial dysplasia. The combination of big data in pathology and artificial intelligence (AI) will facilitate the achievement of accurate diagnoses and treatments, providing objective and efficient methods to integrate and refine diverse morphological, molecular, and multi-omics information. This perspective provides a summary of the existing research and prospects for the application of AI to epithelial dysplasia in multiple organs. A number of studies have been conducted with the aim of developing a grading system and prognostic identification method for epithelial dysplasia in the oral cavity, larynx, esophagus, and stomach. Digital pathology-based AI may prove useful in facilitating the clinical management of epithelial dysplasia in multiple organs. In summary, digital pathology images obtained by scanning hematoxylin & eosin-stained slides, identifying image features, and building AI models using deep learning combined with machine learning algorithms, validated with real-world data from multicenter cohorts could provide AI as a promising clinical application in the future.