Application of Artificial Intelligence to Oral Diseases
A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Machine Learning and Artificial Intelligence in Diagnostics".
Deadline for manuscript submissions: 30 November 2025 | Viewed by 6
Special Issue Editor
Special Issue Information
Dear Colleagues,
AI technologies exhibit remarkable vitality in the diagnosis, treatment planning, and outcome prediction of oral diseases. This Special Issue, dedicated to the "Application of Artificial Intelligence to Oral Diseases", aims to highlight the latest advancements, challenges, and future directions in leveraging AI to enhance the diagnosis, treatment, and management of oral diseases. As AI technologies, including machine learning, deep learning, computer vision, and natural language processing, continue to evolve, their integration into dentistry offers unprecedented opportunities for improving patient care, streamlining workflows, and advancing precision medicine in oral health.
Scope and Topics of Interest
This Special Issue seeks the submission of high-quality original research articles, systematic reviews, case studies, and perspective papers that explore the intersection of AI and oral healthcare. Topics of interest include, but are not limited to, the following:
- AI in Diagnostic Imaging: Automated analysis of dental radiographs, cone beam computed tomography (CBCT), intraoral scans, and optical imaging for detecting caries, periodontal disease, periapical lesions, and oral cancers.
- Early Detection and Risk Prediction: Machine learning models for predicting disease progression (e.g., periodontitis, oral squamous cell carcinoma) and personalized risk assessment.
- Treatment Planning and Robotics: AI-assisted decision support systems for implantology, orthodontics, and maxillofacial surgery, including robotic-assisted interventions.
- Natural Language Processing (NLP): Applications in electronic health records (EHRs), clinical note analysis, and automated patient communication.
- Teledentistry and AI: Remote monitoring, AI-powered chatbots for patient triage, and mobile-based diagnostic tools.
- Ethical, Legal, and Regulatory Considerations: Challenges in data privacy, algorithmic bias, and the clinical validation of AI models in dentistry.
This Special Issue provides a platform for interdisciplinary collaboration among dentists, computer scientists, engineers, and policymakers to discuss innovations that bridge the gap between AI research and clinical practice. Accepted papers will contribute to a growing body of knowledge that could redefine the standards of care in oral medicine.
Prof. Dr. Gang Li
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- oral disease
- artificial intelligence
- AI-driven diagnosis
- oral radiology
- cone beam computed tomography (CBCT)
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