The remarkable achievements of Artificial Intelligence (AI) across various sectors have not only garnered attention but are also driving the development of AI systems in medicine, particularly in dentistry. The human brain is an intricate network of interconnected neurons that relay signals throughout the body. The quest to emulate this complex structure has led to significant advancements in AI. AI, a field of computer science, involves creating intelligent software or machines capable of executing tasks that typically require human intelligence. AI technologies are increasingly expected to be employed for gathering, processing, and organizing patient-related data to facilitate patient-centered, personalized dental treatments. Therefore, it is crucial for dental professionals to be informed about the potential implications of AI to enhance the profitability and effectiveness of clinical practices in the future. This review explores some of the current and future applications of AI in dentistry.
Introduction
The inherent human pursuit to work smarter, not harder, has catalyzed the emergence of Artificial Intelligence (AI). This term has become widely recognized due to its broad and somewhat generalized application. In essence, AI encompasses algorithms that mimic human cognitive processes to solve problems, yet understanding its full concept extends beyond mere mathematical or engineering solutions—it demands profound scientific insight. Intelligence is defined as the capability of a system to act suitably in an uncertain environment, with suitable actions being those that enhance the likelihood of success.
The phrase “artificial intelligence” was first introduced on August 31, 1955, by pioneers John McCarthy, Marvin L. Minsky, Nathaniel Rochester, and Claude E. Shannon through their proposal for the Dartmouth Summer Research Project on Artificial Intelligence. AI is now heralded as the fourth industrial revolution, utilizing computer technology to replicate human-like critical thinking, decision-making, and intelligence.
In healthcare, AI manifests in two forms: virtual and physical. Virtual applications of AI include disease diagnosis, scheduling appointments, managing drug interactions, maintaining electronic health records, and enhancing medical imaging. On the physical side, AI contributes to healthcare through rehabilitation aids, telepresence, robotic assistance in surgeries, and robots designed for elderly care.
Although the last two decades have seen a growing interest in dental AI, its integration into routine practice is still in its infancy. This review seeks to explore the literature on AI applications across all dental disciplines, particularly in the fields of prosthodontics, aiming to improve clinical decision-making and predict successful treatments, while also identifying current limitations in AI usage within dentistry.
AI at Zora is conceptualized under two primary frameworks: weak AI, which deals with simulation of human thought processes in specific applications, and strong AI, which we are advancing towards, aiming to fully replicate human cognitive abilities in machines. Our research focuses on developing AI that not only supports existing dental practices but also opens new avenues for treatment and patient interaction.
AI systems at Zora undergo extensive phases of training and testing, ensuring they are robust and reliable for clinical application. These systems are crafted to learn from vast datasets, encompassing a wide range of dental conditions and scenarios, thereby improving their diagnostic and operational capabilities over time.
Application of Artificial Intelligence In Dentistry
Since its development in the 1980s, the field of artificial intelligence (AI) in education has significantly evolved. Augmented reality (AR) and virtual reality (VR) are now extensively used in dental education to simulate real-life clinical scenarios without the associated risks of practicing on live patients. However, the incorporation of AI in prosthodontics remains limited despite the field's complexity and diversity, which stand to gain substantially from the routine application of AI technologies.
Radiologic and Diagnostic Applications:
AI can be integrated with advanced imaging systems such as MRI and Cone Beam Computed Tomography (CBCT) to detect subtle deviations that might be overlooked by the human eye. This capability extends to accurately identifying landmarks on radiographs. In orthodontics, AI has the potential to predict tooth movement by analyzing patient-specific ethnic and anthropological data.
Artificial Neural Networks (ANNs) serve as a valuable second opinion for locating the minor apical foramen, thus improving the accuracy of determining working lengths in radiographs and diagnosing proximal dental caries. Convolutional Neural Networks (CNNs) have shown a high precision rate of 95.8–99.45% in identifying and detecting teeth, a performance that rivals that of clinical experts.
In a study involving 3000 periapical radiographs of posterior teeth, a deep CNN algorithm detected carious lesions with an accuracy of 75.5–93.3% and a sensitivity of 74.5–97.1%. This marked an improvement over traditional clinical diagnosis using radiographs alone, which showed a sensitivity range of 19% to 94%. In another study, a deep CNN-based Computer-Assisted Diagnosis (CAD) system was used for detecting osteoporosis using panoramic radiographs, demonstrating very promising results.
Further applications of CNNs include the detection of Sjogren's syndrome (SjS) on CT images, where the results surpassed the diagnostic performance of radiologists. Another application saw the use of deep learning for diagnosing maxillary sinusitis on panoramic radiography, showcasing the expanding capabilities of AI in dental diagnostics.
AI-powered software like Second Opinion, Pearl, Denti.AI, and VideaDetect employ machine learning algorithms to interpret dental radiographs. These programs assist clinicians by automatically generating treatment proposals based on the data analyzed by deep learning algorithms. However, the scope of these automated treatment plans currently extends only to basic procedures such as fillings, and partial and full coverage restorations.
In 3D radiographic analyses, such as those obtained from tomography scans, AI can annotate anatomical landmarks and segment structures of the bone and teeth. For instance, Orca-Dental AI has introduced software capable of automatically segmenting anatomical structures like the maxilla, mandible, and teeth. This software also enables nerve recognition and the identification of pathological conditions, further enhancing the utility and accuracy of AI in dental diagnostics and treatment planning.
Artificial Intelligence In Removable Prosthodontics
Digital technologies such as CAD/CAM (Computer-Aided Design and Computer-Aided Manufacturing) are increasingly utilized in the creation of removable dental prostheses and complete dentures. These technologies offer substantial advantages in the dental fabrication process, including enhanced precision and efficiency.
One significant benefit of AI in this context is its capability to analyze and learn from a vast database of doctor-approved designs, which are continuously updated and stored in the cloud. This allows for detailed evaluations of dental aesthetics based on a vast array of dental anatomy data.
To craft the ideal aesthetic prosthesis for a patient, various factors are considered, including anthropological data, facial measurements, ethnicity, and individual preferences. These elements are integrated using RaPiD, a design assistant tool for prosthodontics. RaPiD utilizes a logic-based framework to amalgamate computer-aided design with knowledge-based systems and databases. With AI's assistance, this tool guides dentists throughout the digital impression process, helping to achieve the best possible impression.
In the realm of CAD/CAM dentures, innovations have been made using pre-polymerized PMMA blocks and 5-axis milling processes, which significantly reduce the number of clinical visits required. This method also decreases the likelihood of porosities, thus enhancing the overall fit of the denture.
Furthermore, Takahashi et al. have explored the application of Convolutional Neural Networks (CNNs) using ImageNet software for the classification and design of dental arches. In this system, a large dataset of classified arch types trains the AI, which then formulates classification rules. These rules are continuously refined through repeated learning cycles. After the learning phase, the AI system applies these rules to new dental arch images to predict classifications. Ultimately, clinicians assess the accuracy of these AI-generated predictions to ensure their validity.
Overall, the integration of CAD/CAM and AI technologies in dental prosthodontics not only streamlines the manufacturing process but also enhances the customization and fitting of dental prostheses, aligning with individual patient needs and aesthetic preferences.
Fixed Dental Prosethesis And Artificial intelligence
For a dental restoration to be effective, it is crucial that the margins and finish lines of the tooth preparation are precisely executed. If these margins are clearly visible and the intraoral scan is accurate, specialized software can automatically delineate the preparation margins and finish lines with high precision. Once these margins are marked, the digital design and milling processes can proceed. An AI-based software, such as the Glidewell in-office solution offered by Glidewell, facilitates the automation of designing single posterior crowns directly in the lab.
Artificial intelligence models serve as powerful tools to enhance various aspects of dental restoration, including selecting the correct tooth shade, automating the design of restorations, accurately mapping out the finish lines, and refining the manufacturing and casting processes. These advancements not only improve the quality and efficiency of dental restorations but also contribute to standardizing procedures within the industry.
Furthermore, dental service organization managers can leverage this technology to evaluate the performance of dental practitioners. By analyzing data generated by these AI systems, managers can identify which practitioners may require further training and which are performing exceptionally, thereby helping to ensure high standards of clinical practice are maintained.
Implant System Identification Using AI
Artificial intelligence algorithms serve as a robust diagnostic tool for identifying dental implants using radiographic images. These AI systems can predict implant survival rates and assist in optimizing dental implant designs. The compatibility of implant systems varies, with some systems not being interchangeable across different brands while others offer broader compatibility. Such compatibility considerations are crucial for the maintenance of implant prostheses.
Recent studies have leveraged deep learning and convolutional neural networks (CNNs) to identify different dental implant systems, achieving accuracy rates between 0.80 and 0.95. For example, a study by Sukegawa et al. utilized deep CNNs to accurately classify 11 different dental implant systems from digital panoramic X-ray images, even under varied conditions at the implant-treatment stage. Advanced models like VGG16 and VGG19 demonstrated exceptional classification performance, and techniques such as Grad-CAM helped reveal how each network layer processed the implant images, providing deeper insights into the features recognized by the AI.
From the initial raw images obtained via orthopantomograms (OPGs) or periapical radiographs, the area of interest is cropped to create datasets for training, validation, and testing. This data is then processed using sophisticated AI models like GoogleNet Inception v3, which parses the information through multiple layers of neural networks.
Furthermore, the precision in implant positioning—considering mesiodistal, apicocoronal, and buccolingual orientations—is vital for the success of the prosthesis. One of the innovative technologies enhancing this process is dynamic navigation, which allows for the placement of implants with an accuracy comparable to that achieved with stereolithographic guides. This system supports real-time tracking and precise implant placement, where the virtual drill is visualized on-screen, enabling the operator to see the drilling progress in three dimensions. This technology not only enhances the accuracy but also significantly improves the overall outcomes of dental implant procedures.
Smile Design and AI
Smile design has become an essential tool for enhancing team communication and boosting patient motivation. Currently, approximately 15 smile design software applications are available to clinicians. These programs depend on the inputs and preferences of the clinician to determine the future smile's shape and alignment. Recently, a new interactive cloud-based platform called Smile Cloud, developed by ADN3D Biotech, was introduced. This platform integrates digital smile design, treatment planning, and facilitates communication among clinicians, technicians, and patients.
Once patient data, including photos and videos, are uploaded, the platform's AI engine analyzes and suggests natural teeth shapes and alignments. Clinicians can then adjust these proposals to refine the smile design further. The finalized design can be converted into an STL file, used to create mock-up models, preparation guides, or surgical guides.
To ensure the aesthetic prosthesis meets patient expectations, the design process incorporates various factors such as anthropological calculations, facial measurements, patient ethnicity, and personal preferences. This is facilitated by a design assistant tool named RaPiD, utilized in prosthodontics. A novel aspect of this process involves the REBEL system, a digital lab that transforms 2D designs into 3D constructs and produces a digital wax-up instantly.
Leveraging AI, the design assistant uses the VisagiSMile concept, which correlates the patient's facial perception and personality with the smile design. This system employs algorithms to calculate the optimal arrangement of incisal silhouette, tooth axis, centrals' dominance, and the combination of individual tooth shapes from thousands of possibilities, ensuring a tailored and visually appealing outcome.
Improving Patient Experience with AI
The crux of improving patient experience lies in effective communication. Zora's AI model leverages natural language processing to understand and respond to patient inquiries with accuracy and empathy. This AI system is trained on a vast array of dental health dialogues and scenarios, enabling it to address a wide range of patient concerns, from treatment procedures and dental hygiene to post-operative care.
For example, consider a patient who is anxious about an upcoming procedure such as the installation of dental implants. Traditionally, this might require extensive consultations, which can be time-consuming for both the patient and the dental professionals. With Zora’s AI system, the patient can interact through a digital platform, receiving instant responses that are tailored to alleviate their specific concerns. The AI can explain the procedure in a detailed, easy-to-understand manner, provide personalized pre-procedure preparations, and even offer post-care instructions based on the specific treatment plan.
Imagine a scenario where a patient named John queries the AI about the care required after a tooth extraction. John types his question into the Zora clinic’s online portal, and the AI, utilizing its deep learning capabilities, comprehends the context of the query and checks John’s treatment history. It responds with customized care instructions, noting that John has a history of sensitivity and recommending specific products and techniques suited for sensitive patients. The AI also reminds John of his follow-up appointment, offering to reschedule if the suggested time is inconvenient.
This interaction not only saves time for both the patient and the dental staff but also enhances John’s confidence in the care he is receiving, making him feel more valued and understood. This level of personalized communication ensures that patients are well-informed, less anxious, and more engaged in their treatment processes.
Zora's AI system is designed to learn continuously from each interaction, improving its responses over time and staying updated with the latest in dental care practices and guidelines. This ensures that the communication remains relevant, accurate, and highly customized to each patient's needs.
Through the development of a Large Language Model in collaboration with OpenAI's GPT-4 Turbo, Zora is transforming how dental professionals interact with patients, making the exchange more informative, responsive, and personalized.
Comments