Reshaping Dental Care with Artificial Intelligence

Artificial intelligence has transformed industries worldwide in recent years, and dentistry is no exception. The concept of machines being able to carry out human jobs is known as “artificial intelligence” (AI).¹ By mimicking human intelligence, AI enhances rather than replaces human expertise.² AI’s integration into dental practices has revolutionized patient care, from appointment scheduling to follow-up procedures, by improving disease detection, treatment methods, and access to care.³ Dental practices reliant on digital technologies like computers and X-ray machines, benefit significantly from AI, enhancing efficiency and patient outcomes. Ongoing research continues to advance AI’s capabilities in dentistry. Machine learning (ML) is a type of AI that allows computer systems to learn from past experiences or data without being explicitly programmed. One specific type of ML technique, Artificial Neural Networks (ANNs), is designed to mimic brain function, enabling computers to learn autonomously without human intervention. Deep Learning (DL) is a subgroup of ANNs that involves multi-layered networks, allowing computers to process complex information. DL techniques, particularly convolutional neural networks (CNNs), are well-suited for tasks like recognizing and analyzing dental images.¹ This article aims to explore current AI applications in various dental specialties, emphasize collaborative partnerships with human expertise, envision future directions, demonstrate efficiency gains, and offer a detailed overview of AI’s role in enhancing patient outcomes, serving as a valuable resource for dental practitioners and researchers.

General Dentistry (Fig. 1)

AI plays a crucial role in modern dental practices by providing easy access to electronic health records (EHRs) and assisting in the prompt detection of abnormalities. It enhances efficiency and precision in dental care through AI-driven virtual dental assistants, which streamline administrative tasks and aid in diagnosis and treatment planning. AI also helps shorten chairside time, improve infection control, and ensure high-quality treatment. Innovations such as medical scribe websites further streamline documentation processes by automatically transcribing patient conversations into SOAP notes.⁴

Prosthodontics (Fig. 2)

AI revolutionizes prosthodontics by optimizing personalized care through data management. Convolutional Neural Networks (CNNs) predict and categorize dental arches, guiding tailored designs for partial dentures.⁵ AI aids in creating crown occlusal surfaces, complete denture designs, and optimized implantology profiles, while automating jaw connection registration for treatment simulations. Teamed with CAD/CAM technology, AI enhances prostheses aesthetics and reduces failure rates.⁶ AI-driven tools improve diagnostics, crown and denture precision, and prolong prosthetic longevity and functionality.⁷ Intraoral scanners, powered by AI, ensure accurate digital impressions, expediting clinical and lab workflows.⁸ This integration accelerates design and manufacturing, adhering to patient-centric care principles.⁹

Endodontics (Fig. 3)

AI revolutionizes endodontics, offering precise diagnostics and treatment planning with remarkable accuracy.¹⁰ ML algorithms optimize root canal treatment, predicting personalized instrumentation and irrigation protocols, leading to successful outcomes and fewer complications.¹¹ Innovations like Navident offer user-friendly, precise solutions for virtual planning in endodontics, enhancing procedural precision, while AI’s clinical applications in the field include detecting root fractures, periapical pathologies, and assessing root morphology to improve procedural outcomes, with guided endodontic platforms further enhancing navigation and treatment planning to ensure ideal results.^12-14

Periodontology (Fig. 4)

AI enhances periodontics by improving image analysis and diagnostic accuracy, with deep learning interpreting alveolar bone and assessing disease severity. ANNs classify periodontitis types, while machine learning ML corrects imaging errors and detects caries. Mask R-CNN is crucial in CBCT scans for precise dental implant planning and identifying anatomical structures, and for calculating radiographic bone loss rates to optimize implant assessments.¹⁵

Orthodontics (Fig. 5)

AI plays a vital role in orthodontic treatment by identifying anatomic landmarks across radiographic modalities, aiding in precise treatment planning and optimization.¹⁶ DL evaluates maxillary asymmetry and forecasts orthodontic needs using radiographic scans, analyzes 3D dental models, and optimizes treatment duration, while the YOLO method diagnoses malocclusion with accuracy and precision.¹⁷ AI-driven orthodontic software generates personalized treatment plans, particularly evident in clear aligner design, ensuring optimal alignment and treatment efficiency.¹⁸

Pediatric Dentistry (Fig. 6)

The AI system demonstrated a performance that was clinically acceptable for identifying dental plaque on primary teeth, comparable to that of a skilled pediatric dentist.¹⁹ In the field of pediatric dentistry, AI holds considerable promise for transforming behavioral practices; tools such as 4D goggles, films, animations, and virtual reality games have proven to be effective behavioral modification aids for young patients.²⁰

Dental Anesthesiology (Fig. 7)

Computer-assisted systems in dental anesthesia help regulate injection pressure and strength for reduced discomfort and improved patient comfort during local anesthetic administration. A scoping review outlined six main clinical applications of AI in dental anesthesiology, such as monitoring and controlling anesthesia, predicting risks, guiding ultrasonography, pain management, and improving operating room logistics.²¹ However, research on AI’s impact on clinical treatment in dental anesthesia is limited, with few studies examining its integration into regular clinical workflows.²²

Oral Surgery (Fig. 8)

AI shows promise in oral maxillofacial surgery, aiding in robotic cranial surgeries with positive outcomes. AI tools utilizing cephalometric measurements and imaging scans support treatment decision-making during orthodontic surgeries for patients with dentofacial deformities, although standardizing these AI assessments remains challenging.²³ AI predicts third molar eruption potential from panoramic radiographs, aiding tooth extraction decisions,²⁴ while integrating VR and IoT enhances surgical planning with 3D visualizations and improved device connectivity, and VR additionally improves patient education and decision-making participation.²⁵

Oral Radiology (Fig. 9)

AI effectively identifies impacted supernumerary teeth on panoramic radiographs and aids in detecting various dental conditions, including cysts, tumors, and periodontal disease, through DL techniques.^{26, 27} DL algorithms integrated into CAD systems assist in diagnosing periodontal bone loss and osteoporosis based on panoramic photographs, revolutionizing clinical and X-ray diagnoses. CBCT provides detailed three-dimensional images, aiding in diagnosing impacted teeth, temporomandibular joint disorders, and jawbone pathologies with superior accuracy.²⁸

Oral Medicine (Fig. 10)

AI-based models, particularly those using Mask R-CNN ResNeXt-FPN, enhance oral lesion classification from clinical images, improving early detection and diagnostic accuracy of premalignant lesions and cancer.²⁹ Utilizing vast biomarker data, AI streamlines the detection and classification of dental conditions, including root caries, BRONJ, and facial defects, in radiographs and aids in the prompt diagnosis and treatment of periodontal disease, sinusitis, arthritic changes in TMJ disorders, and Oral Squamous Cell Carcinoma.³⁰

Oral Pathology (Fig. 11)

Limited research exists on AI’s role in diagnosing potential cancerous or premalignant head and neck lesions, yet AI and ML methods show effectiveness akin to traditional histopathology, offering faster, unbiased, and reproducible evaluations.³¹ AI has shown promise in early oral cancer detection using laser-induced autofluorescence spectra and artificial neural networks.³² CNN-based models like DenseNet-169 and ResNet-101 matched or surpassed expert-level performance in classifying oral cancers and oral potentially malignant disorders (OPMDs), offering a promising diagnostic tool for enhancing early detection in screening programs.³³

Orofacial Pain (Fig. 12)

AI assists Orofacial Pain Specialists by analyzing patient-reported data, aiding in diagnosing various orofacial pain conditions and developing tailored treatment strategies.³⁴ It is pivotal in the multifaceted diagnosis and treatment of Temporomandibular Disorders (TMD), including the design of orthotic devices and the classification of sleep disorders such as obstructive sleep apnea (OSA).^{35, 36} AI-driven tools, including ANN and CNN, support precise diagnosis and development of targeted treatments, significantly improving clinical decision-making and treatment accuracy.^{37, 38}

Dental Public Health (Fig. 13)

AI is pivotal in preventive dentistry, aiding early interventions and ongoing patient data monitoring. It optimizes preventive treatment planning like resin restoration, enhancing long-term oral health. Mobile health apps in dental public health, empowered by AI-driven data analysis, elevate patient engagement and education. AI’s predictive analytics leverage extensive datasets to forecast dental health trends and identify at-risk groups, vital for crafting targeted preventive programs that cut health costs and boost public outcomes.³⁹ While unsupervised machine learning progresses, primary care health informatics is crucial for safe AI integration in dental practices. AI’s evolution could revolutionize routine screening and specialized diagnostics in medicine and public health in underserved areas.^{40, 41}

Practice Management (Fig. 14)

AI streamlines practice management by optimizing appointment scheduling, enhancing resource efficiency, reducing no-shows, and enhancing patient experiences. Tools like chatbots and virtual assistants provide personalized interactions and reminders. AI also automates HIPAA-compliant consent forms, extracts data using NLP, manages insurance data, streamlines claims processing, and facilitates secure payment processing, simplifying administrative tasks and improving financial operations.⁴²

Future Directions (Fig. 15)

The paper envisions AI’s potential applications in dentistry, including advancements in lesion detection, early prediction, enhanced image quality, and reduced radiation exposure, promising to enhance the overall patient experience in dental clinics.

Conclusion

Artificial intelligence profoundly transforms dentistry, improving diagnostic accuracy, treatment planning, and patient care. The collaborative partnership between AI and human expertise augments dental professionals’ capabilities, driving efficiency, innovation, and improved outcomes in oral healthcare. Envisioning future advancements like improved lesion detection and image quality underscores AI’s ongoing evolution in reshaping modern dentistry for the better. 

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About the Author

Dr. Amey G. Patil, a cosmetic dentist and board-certified orofacial pain specialist, is Assistant Professor and Director, General Dental Concepts at the Temporomandibular Disorders and Orofacial Pain Center, Diagnostic Sciences, at Rutgers. He is a Diplomate of the American Board of Orofacial Pain (DABOP) and Fellow, International College of Dentists (FICD), American College of Dentists (FACD), Pierre Fauchard Academy (FPFA), International Academy for Dental-Facial Esthetics (FIADFE), and American Academy of Orofacial Pain (FAAOP). The inventor of the pico-hydroelectric toothbrush, Dr. Patil speaks internationally on AI, esthetics and orofacial pain.