In Which Areas is Artificial Intelligence Used in Dentistry?
With the rapid advancements in technology, artificial intelligence (AI) has become a widely used technology across many aspects of modern life. AI systems are utilized in various sectors, including industry, manufacturing, finance, education, transportation, and communication, where they can analyze vast amounts of data in a short time, identify specific patterns, and support decision-making processes.
Artificial Intelligence and the Healthcare Sector
One of the sectors significantly impacted by this transformation is healthcare. Artificial intelligence technologies play an important role in various stages of healthcare services, ranging from medical image analysis and clinical data evaluation to treatment planning and patient monitoring. These technologies serve as supportive tools that assist healthcare professionals in their clinical decision-making processes.
Artificial Intelligence in Dentistry
Dentistry is among the healthcare fields where the use of artificial intelligence is rapidly expanding. Thanks to digital imaging systems, intraoral scanners, and AI-assisted analysis software, many procedures can now be planned and performed in a more predictable and organized manner. However, it remains essential that the results generated by these technologies are interpreted alongside the dentist’s clinical evaluation.
AI-Assisted Applications in Dentistry
Artificial intelligence technologies can be utilized across various dental specialties for different purposes. Their applications range from digital smile design and radiographic image analysis to the assessment of periodontal diseases, pediatric dentistry, and orthodontic treatment planning. In addition, digital impression systems, CAD/CAM manufacturing technologies, and patient follow-up processes are among the areas benefiting from AI-supported software. The most common applications of AI in dentistry include:
- Digital smile design and aesthetic treatment planning
- Digital intraoral impression systems
- AI-assisted analysis of radiographic images
- Assessment of periodontal (gum) diseases
- Pediatric dentistry applications
- Orthodontic diagnosis and treatment planning
- Preventive dentistry applications
- Treatment planning and patient follow-up processes
Digital Smile Design and Aesthetic Planning
In aesthetic dentistry, artificial intelligence is used to support treatment planning. Facial photographs and digital intraoral scans can be analyzed together to evaluate facial proportions, lip contours, tooth positioning, and anatomical structures visible during smiling. Based on these analyses, different tooth shapes can be digitally created to simulate potential treatment outcomes. This allows patients to visualize the planned restoration before treatment begins.
Whether the proposed design will ultimately be applied depends on both the patient's expectations and the dentist's clinical assessment. AI-supported digital planning systems can also facilitate digital data transfer between the dental clinic and the laboratory. In some cases, this may reduce the need for repeated impressions and contribute to a more efficient treatment planning process.
Digital Intraoral Impression Systems
Traditional impression techniques using silicone or plaster-based materials may trigger the gag reflex in some patients. Modern digital intraoral scanners can capture three-dimensional images of the teeth and oral tissues directly into a computer system. AI-supported software can detect incomplete scan areas or regions that may compromise image quality, providing real-time alerts to the operator. This enables the necessary areas to be rescanned, thereby improving the accuracy of the digital impression. However, digital impression systems may not offer the same advantages for every patient. The appropriate method should be determined by the dentist based on the patient's oral condition and the planned treatment.
Radiographic Image Analysis
Radiographic imaging is a fundamental component of diagnosis and treatment planning in dentistry. AI-assisted image analysis systems can help evaluate dental caries, bone levels, impacted teeth, and certain anatomical structures on digital radiographs. These software programs utilize artificial intelligence algorithms trained on large datasets and can automatically highlight findings that may require closer examination, thereby supporting the clinical evaluation process. However, these findings alone do not constitute a diagnosis. Radiographic interpretations should always be considered alongside the patient's clinical examination, symptoms, and other diagnostic findings.
Periodontology (Gum Diseases)
Artificial intelligence-assisted systems can also be used in the evaluation of periodontal diseases. Bone levels can be analyzed on digital radiographs, while measurements related to gingival recession and periodontal pockets can be recorded. Current findings can be compared with previous examination data to generate graphical assessments of disease progression. These data may support the dentist in monitoring the patient and developing an appropriate treatment plan. Nevertheless, the final treatment approach is determined by considering the stage of the disease, oral hygiene status, systemic health, and clinical examination findings together.
Pediatric Dentistry
Treatment planning for pediatric patients varies depending on age, developmental stage, level of cooperation, and oral health status. AI-supported systems can contribute to risk assessment by analyzing previous treatment records, caries experience, oral hygiene habits, and radiographic findings. Based on these evaluations, preventive measures can be planned, routine follow-up intervals can be determined, and caries risk can be monitored. However, preventive treatment strategies should always be tailored to each child's individual clinical assessment.
Orthodontic Planning
In orthodontics, artificial intelligence can be used to assess jaw development, analyze tooth alignment, and create digital treatment plans. Particularly in growing children, potential tooth movements can be simulated using digital records. Different treatment scenarios can also be digitally planned for clear aligner therapy and other orthodontic approaches. Although these simulations can provide valuable predictions about the treatment process, actual clinical outcomes may vary depending on the patient's growth potential, biological response, and compliance with treatment.
Contributions of Artificial Intelligence to Dentistry
AI-supported systems can contribute to the more efficient management of clinical workflows in dentistry. Through digital treatment planning, image analysis, and evaluation of patient records, certain procedures can be completed more efficiently. Treatment plans can be visually presented to patients, and follow-up processes can be managed in a more systematic manner.
However, artificial intelligence is not a replacement for the dentist. All AI-generated data must be interpreted alongside the clinical examination, radiographic findings, and the patient's overall health status. The final treatment method and treatment planning are determined based on the dentist's individual clinical judgment. The benefits offered by artificial intelligence and treatment outcomes may vary depending on each patient's unique clinical characteristics.
