The field of periodontics stands on the brink of a technological revolution, with artificial intelligence (AI) poised to transform every aspect of patient care. As we look towards the next decade, AI promises to enhance diagnostic accuracy, personalize treatment plans, streamline clinical workflows, and improve long-term patient outcomes. This article explores five key areas where AI is set to significantly impact periodontal practice, supported by current research and clinical evidence.
As clinicians and professionals of the future, we must stay informed about these emerging technologies and consider their integration into our practices. The potential benefits are immense, offering us personalized learning experiences and expert interaction. By understanding and embracing these innovations, we can ensure that our field remains at the forefront of dental care, offering patients the most advanced and effective treatments possible.
1. Enhanced Diagnostics and Imaging Analysis
AI-powered diagnostic tools are revolutionizing how we detect and assess periodontal disease. With their potential to significantly enhance diagnostic accuracy, particularly in advanced imaging analysis, these tools are at the forefront of a transformation in radiography.
Cone Beam Computed Tomography (CBCT) combined with AI algorithms is dramatically improving our ability to visualize and analyze periodontal structures. AI can automatically detect and highlight abnormalities such as bone loss, calculus deposits, and other pathologies with unprecedented accuracy. Software platforms like Pearl, Overjet, DeepCare, and Diagnocat are leading this charge, offering tools that can analyze full-mouth series radiographs in seconds. The results offered by these programs augment the clinician’s ability to assess areas they typically do not focus on. For example, a periodontist may not be interested in detecting a pulp stone in a radiographic analysis, however, this is essential information for the endodontist.
Research by Lee et al. (2018) demonstrated that AI algorithms could diagnose periodontally compromised teeth with an accuracy rate between 76.7% and 81.0%, rivalling that of experienced clinicians. Similarly, Krois et al. (2019) found that deep learning algorithms could detect periodontal bone loss on dental radiographs with high accuracy, potentially surpassing human capabilities in some cases.
The clinical implications are profound. Early detection of subtle signs of periodontal disease allows for more timely interventions, potentially halting disease progression before significant damage occurs. For example, in a case of early-stage aggressive periodontitis, AI analysis might detect minor bone loss patterns that could be easily overlooked in standard radiographic assessment, prompting earlier and more targeted treatment.
On the forefront is a predictable AI-augmented analysis of Cone Beam Computed Tomography (CBCT) images to measure clinical probing depths and provide a new clinical parameter in periodontics- AI-CBCT Virtual Probing Depth (AI-CBCT VPD). This novel measurement technique utilizes artificial intelligence algorithms to analyze CBCT scans and estimate periodontal probing depths without the need for clinical probing.
Interestingly, the potential exists to assign a relative “grade” to a patient’s overall oral health using AI-augmented technology simply from a panoramic film (DeepCare.com). The potential to assign a “grade” to the quality of restorative, endodontic, implant and orthodontic treatment is also possible with many of the current AI-imaging programs.
However, it’s crucial to note that while AI can enhance our diagnostic capabilities, it does not replace clinical judgment. As clinicians, we must integrate AI insights with our expertise, patient history, and clinical examination findings to make comprehensive diagnoses and treatment decisions. The responsibility to the patient still rests with the dentist and cannot be shifted to the technology. AI is a tool to assist us, not a replacement for our professional judgment.
2. Personalized Treatment Planning and Predictive Analytics
AI’s ability to analyze vast amounts of data and identify patterns is ushering in an era of highly personalized treatment planning. This approach, often referred to as “P4 Dentistry” (Predictive, Preventive, Personalized, Participatory), is set to revolutionize periodontal care.
AI algorithms can assess many factors – including genetic predispositions, oral microbiome composition, medical history, lifestyle factors, and previous treatment responses – to predict disease progression and suggest optimal treatment strategies. This level of personalization was previously unattainable and promises to significantly improve treatment outcomes.
A study by Papantonopoulos et al. (2014) demonstrated the potential of artificial neural networks (ANNs) in distinguishing between aggressive and chronic periodontitis using immunologic parameters. The model achieved 90-98% accuracy in classification, highlighting AI’s potential in complex diagnostic scenarios.
In practice, this could mean developing highly tailored treatment plans. For instance, consider a patient with a history of poorly controlled diabetes and aggressive periodontitis. An AI system could analyze this patient’s data alongside broader datasets to predict the likelihood of rapid disease progression. Based on these insights, a more intensive treatment protocol might be recommended, including more frequent professional cleanings, targeted antimicrobial therapy, and closer monitoring of systemic health markers.
Moreover, AI can help in predicting treatment outcomes. By analyzing data from thousands of similar cases, AI can provide clinicians with probability estimates for different treatment options, aiding in shared decision-making with patients.
3. AI-Driven Documentation and Patient Communication
Efficient documentation and effective patient communication are critical components of successful periodontal practice. AI is playing an increasingly important role in streamlining these processes, offering significant advantages in both time management and patient education while improving the quality of clinical documentation.
AI-powered scribe programs, such as Scribeberry, are transforming the documentation process. These tools use natural language processing (NLP) to transcribe conversations during patient consultations and generate detailed clinical notes in real-time. This allows clinicians to focus more on patient interaction, reducing the administrative burden and enhancing the overall consultation experience. The quality of the record-keeping can be benchmarked to required standards and more thorough documentation can be a byproduct of using an AI-powered scribe program.
Research by Mann et al. (2020) found that the use of AI in documentation reduced the time clinicians spent on paperwork by up to 30%, allowing for more time to be spent on patient care. This efficiency gain can improve patient satisfaction and potentially allow more patients to be seen without compromising care quality.
Regarding patient communication, AI enables the creation of personalized educational materials. By analyzing patient data, AI can generate content that addresses specific concerns, explains treatment plans in layman’s terms, and provides tailored oral hygiene and post-operative instructions. This personalization can significantly improve patient understanding and treatment adherence. For example, after a soft tissue graft consultation, the scribe program can be prompted, “Create a brochure for a 45-year-old engineer who appreciates details to summarize our consultation and review the connective tissue graft procedure.” The brochure would contrast this prompt: “Create a brochure for a squeamish 17-year-old summarizing our consultation and emphasizing the restrictions post-operatively.”
Moreover, after a comprehensive periodontal examination, an AI-powered scribe system could generate a custom brochure for the patient that might include 3D visualizations of the patient’s specific condition, explain the recommended treatment plan using analogies tailored to the patient’s interests or profession, and provide a personalized home care routine based on the patient’s lifestyle and specific periodontal needs.
4. Long-Term Patient Monitoring and Disease Prevention
One of the most exciting applications of AI in periodontics is in long-term patient monitoring and disease prevention. AI-driven platforms can analyze data from various sources – including electronic health records, regular check-ups, and even wearable devices – to continuously monitor patients’ periodontal health.
Predictive models can alert both the clinician and the patient to potential issues before they become serious, allowing for timely intervention. This shift from reactive to proactive care has the potential to significantly improve long-term outcomes and reduce the incidence of severe periodontal disease.
Emerging technologies, such as AI-powered smart toothbrushes and oral sensors, are at the forefront of this trend. These devices can collect real-time data on oral health indicators like plaque levels, gingival inflammation, or even biomarkers in saliva. AI algorithms can then analyze this data to detect early signs of periodontal disease or potential complications.
For instance, a patient with a history of periodontal disease might use a smart toothbrush that tracks brushing habits and gingival health. If the AI system detects a decline in oral hygiene, it could automatically notify both the patient and potentially the clinician. The system might then suggest an earlier recall appointment or provide the patient with targeted oral hygiene advice.
While research in this area is still emerging, preliminary studies are promising. A pilot study by Leung et al. (2021) demonstrated that AI-powered oral health monitoring systems could accurately detect early signs of gingivitis, potentially allowing for earlier interventions.
5. AI in Periodontal Education and Training
While not directly related to patient care, AI’s impact on periodontal and dental education and training will have far-reaching effects on the future of our profession. AI is set to revolutionize how new clinicians are trained and examined and how established professionals maintain and upgrade their skills.
AI-powered simulation systems are enhancing hands-on training for periodontal procedures. These systems can provide realistic, haptic feedback, allowing trainees to practice complex procedures in a safe, virtual environment. AI can analyze a trainee’s performance, providing instant feedback and personalized learning recommendations.
Furthermore, AI is being used to develop adaptive learning platforms for continuing education. These systems can assess a practitioner’s knowledge gaps and create customized learning modules, ensuring more efficient and effective professional development.
A study by Schwendicke et al. (2021) highlighted the potential of AI in dental education, noting its ability to provide personalized learning experiences and enhance clinical decision-making skills. As these technologies mature, we can expect to see a new generation of periodontists who are not only skilled in traditional techniques but also adept at leveraging AI tools in their practice.
On the forefront of education is an advanced AI system that serves as a digital replica or avatar of a specific individual, typically an expert or educator such as a professor. A Digital Academic Replica (DAR) is created by training a large language model (like GPT) on a comprehensive dataset of the individual’s knowledge, writings, communications, and personal style.
The result is a highly personalized AI that can:
- Emulate the professor’s teaching style and methods
- Respond to queries with the depth and breadth of knowledge the professor possesses
- Write in a manner consistent with the professor’s style and expertise
- Interact with students or other users in a way that closely mimics the professor’s communication patterns
A DAR acts as a virtual stand-in for the professor, capable of engaging in educational activities, answering questions, and providing insights as if the users were interacting directly with the professor themselves. This technology has the potential to extend the reach and availability of expert knowledge beyond the physical and temporal constraints of the individual professor.
It’s important to note that while a DAR can closely mimic the professor’s knowledge and style, it remains an AI model and cannot truly replicate the dynamic thinking, emotional intelligence, or real-time learning capabilities of a human expert. Nevertheless, it represents a powerful tool for scaling personalized education and expert interaction.
Conclusion
The integration of AI into periodontics offers unprecedented opportunities to enhance patient care, from improving diagnostics and personalizing treatment plans to enabling continuous monitoring and revolutionizing professional education. However, these advancements also bring challenges, particularly in ensuring ethical use, maintaining patient privacy, and avoiding over-reliance on technology.
As we embrace these innovations, it’s crucial to remember that AI should augment, not replace, clinical expertise. The clinician’s role will evolve to include interpreting AI-generated insights, explaining complex data to patients, and making nuanced decisions that consider both AI recommendations and human factors.
The next decade promises to be an exciting time for periodontics. By staying informed about AI advancements and thoughtfully integrating these technologies into our practices, we can provide our patients with more accurate diagnoses, more effective treatments, and better long-term outcomes. The future of periodontics is here, and it’s powered by AI. 
Oral Health welcomes this original article.
Acknowledgement: The author extends his sincere gratitude to Dr. Izchak Barzilay and Dr. John Zarb and for their invaluable contributions to the development of this paper. Their expertise in implant dentistry, coupled with their forward-thinking approach to AI driven technologies in dentistry, provided crucial insights. I am also deeply indebted to Professor Dera Nevin for her exceptional guidance and expertise in the legal and ethical implications of AI in healthcare. Her contributions through the Global Professional Master of Laws (GPLLM) program at the University of Toronto Faculty of Law were instrumental in addressing the complex intersections of technology, law, and dental practice.
References
- Lee JH, Kim DH, Jeong SN, Choi SH. Diagnosis and prediction of periodontally compromised teeth using a deep learning-based convolutional neural network algorithm. J Periodontal Implant Sci. 2018;48(2):114-123.
- Krois J, Ekert T, Meinhold L, et al. Deep Learning for the Radiographic Detection of Periodontal Bone Loss. Sci Rep. 2019;9(1):8495.
- Papantonopoulos G, Takahashi K, Bountis T, Loos BG. Artificial Neural Networks for the Diagnosis of Aggressive Periodontitis Trained by Immunologic Parameters. PLoS One. 2014;9(3):e89757.
- Mann R, Namiki Y, Sakai K, et al. Artificial Intelligence-Based Approach for Automated Documentation in Dental Care. J Dent Res. 2020;99(Special Issue A):abstract number 2326.
- Leung D, Meng HX, Chao J, et al. Artificial intelligence in gingivitis detection: A pilot study. J Clin Periodontol. 2021;48(S21):73.
- Schwendicke F, Samek W, Krois J. Artificial Intelligence in Dentistry: Chances and Challenges. J Dent Res. 2020;99(7):769-774.
- FDI World Dental Federation. Artificial Intelligence: A game changer for dental care? FDI Policy Statement. 2020.
- American Dental Association. Artificial Intelligence in Dentistry. ADA Council on Scientific Affairs; 2021.
- Nguyen TT, Larrivée N, Lee A, Bilaniuk O, Durand R. Use of Artificial Intelligence in Dentistry: Current Clinical Trends and Research Advances. J Can Dent Assoc. 2021;87:l7.
- Schwendicke F, Golla T, Dreher M, Krois J. Convolutional neural networks for dental image diagnostics: A scoping review. J Dent. 2019;91:103226.
About the Author
Dr. Peter Fritz is a pioneering periodontist and implant surgeon, blending clinical excellence with academic innovation. As Chair of the AI and Emerging Digital Technology Task Force at the Royal College of Dentists of Canada, he is a leader in the integration of cutting-edge technologies in dentistry. Holding adjunct positions at McMaster University and Brock University, Dr. Fritz conducts interdisciplinary research on oral-systemic health connections. His clinic in Fonthill, Ontario, is recognized for redefining patient experiences through collaborative, technology-driven care. With multiple advanced degrees and a perspective enriched by global adventures, Dr. Fritz exemplifies a commitment to advancing dental science through both innovation and exploration.
link