Commentary - Journal of Clinical Dentistry and Oral Health (2025) Volume 9, Issue 1
The impact of artificial intelligence on diagnosis and treatment planning in dentistry
Lara Cosgro*School of Education, Faculty of Humanities and Social Sciences, The University of Queensland, Australia
- *Corresponding Author:
- Lara Cosgro
School of Education, Faculty of Humanities and Social Sciences
The University of Queensland, Australia
E-mail: Luseedrds@uq.edu.au
Received: 07-Jan-2025, Manuscript No. AACDOH- 25-157585; Editor assigned: 08-Jan-2025, Pre QC No. AACDOH- 25-157585 (PQ); Reviewed: 19-Jan-2025, QC No. AACDOH-25-157585; Revised: 20-Jan-2025, Manuscript No. AACDOH- 25-157585 (R); Published: 29-Jan-2025, DOI: 10.35841/aacdoh-9.1.246
Citation: Cosgro L. The impact of artificial intelligence on diagnosis and treatment planning in dentistry. J Clin Dentistry Oral Health.2025;(5):246
Abstract
Introduction
Artificial intelligence (AI) has made significant strides across numerous fields, and dentistry is no exception. Over the past decade, AI's application in dental practices has revolutionized both diagnosis and treatment planning, enhancing precision, efficiency, and patient outcomes. AI encompasses various technologies, including machine learning (ML), deep learning (DL), and natural language processing (NLP), each contributing to different aspects of dental practice.
AI in diagnosis
One of the primary applications of AI in dentistry is in the diagnosis of oral diseases. AI-powered diagnostic tools can analyze medical images, such as radiographs, to detect dental anomalies with remarkable accuracy. For example, AI algorithms have been trained to identify cavities, periodontal diseases, and even oral cancer at early stages, often more effectively than human clinicians. The use of AI in diagnostic radiology has shown promise in identifying minute changes in images that could easily be overlooked by the human eye. This enhanced sensitivity reduces the chances of misdiagnosis and allows for more accurate treatment planning.
Moreover, AI systems are capable of integrating patient data, including medical history, genetic information, and clinical observations, to provide a comprehensive diagnostic assessment. This could lead to the early detection of systemic diseases that manifest in the oral cavity, such as diabetes or cardiovascular diseases, allowing for timely intervention and better overall patient care.
AI in treatment planning
AI also plays a pivotal role in the development of personalized treatment plans. By analyzing vast amounts of data from previous cases, AI systems can predict the most effective treatment strategies for individual patients. For instance, AI models can recommend optimal restorative treatments, such as crowns, implants, or dentures, based on the patient's unique anatomical and clinical conditions. This process not only saves time but also increases the likelihood of successful outcomes by tailoring treatments to the specific needs of the patient. Additionally, AI can aid in the design and customization of dental prosthetics. Through computer-aided design (CAD) and computer-aided manufacturing (CAM) systems, AI algorithms can optimize the fitting of crowns, bridges, and implants, ensuring they align perfectly with the patient's unique oral structure. This contributes to greater comfort, improved function, and enhanced aesthetic outcomes [1-5].
AI in predictive analysis and risk assessment
AI’s ability to perform predictive analysis is another valuable asset in dentistry. By evaluating a patient's clinical data, AI models can predict future dental problems, enabling preventive measures to be taken. For example, AI can assess the risk of periodontal disease or caries development based on factors such as oral hygiene habits, diet, and genetic predisposition. This allows for earlier intervention, potentially reducing the need for more invasive treatments in the future [6-10].
Challenges and limitations
Despite its potential, the integration of AI into dental practices faces several challenges. First, the reliance on large datasets for AI training raises concerns about data privacy and security. Additionally, there is a need for dental professionals to undergo training in the use of AI tools to fully capitalize on their benefits. Moreover, while AI can assist in decision-making, it should not replace the clinical judgment of experienced practitioners. Ensuring a collaborative approach between AI systems and clinicians is crucial for maintaining patient safety and care quality.
Conclusion
In conclusion, artificial intelligence is making significant contributions to the field of dentistry, particularly in improving the accuracy of diagnosis, treatment planning, and predictive analysis. With continuous advancements in AI technology, the future of dentistry looks promising, with potential benefits ranging from enhanced clinical outcomes to improved patient satisfaction. However, its successful integration into dental practice will require careful consideration of ethical, technical, and educational aspects.
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