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References

Kishore M, Panat SR, Aggarwal A Evidence based dental care: integrating clinical expertise with systematic research. J Clin Diagn Res. 2014; 8:259-2562 https://doi.org/10.7860/JCDR/2014/6595.4076
Schwendicke F, Samek W, Krois J. Artificial intelligence in dentistry: chances and challenges. J Dent Res. 2020; 99:769-774 https://doi.org/10.1177/0022034520915714
Chen YW, Stanley K, Att W. Artificial intelligence in dentistry: current applications and future perspectives. Quintessence Int. 2020; 51:248-257 https://doi.org/10.3290/j.qi.a43952
Ding H, Wu J, Zhao W Artificial intelligence in dentistry: a review. Front Dent Med. 2023; 4
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The role of AI in advancing evidence-based dentistry

From Volume 51, Issue 1, January 2024 | Pages 66-67

Authors

Mojtaba Mehrabanian

Alumnus of University of Debrecen, Hungary

Articles by Mojtaba Mehrabanian

Aisan Eskandari-Yaghbastlo

Alumnus of Gulf Medical University, UAE

Articles by Aisan Eskandari-Yaghbastlo

Article

Evidence-based dentistry (EBD) is widely regarded as the gold standard in global oral healthcare owing to the increasing complexity of clinical dentistry. EBD integrates top-quality scientific evidence with clinical expertise and patient values to enhance clinical decision-making.1 Given that medical knowledge is being constantly updated, streamlining the search process is imperative. Finding high-quality clinical care evidence is a demanding task. In recent years, artificial intelligence (AI) has shown great potential in enhancing EBD by uncovering patterns and connections in medical data, big data analysis and evidence synthesis, and aiding clinical decision support.2,3,4

AI can automate time-consuming tasks such as literature searching and screening. Machine learning approaches, for instance, can enhance the efficiency and accuracy of high-quality clinical evidence retrieval in biomedical literature, allowing rapid evidence synthesis.5 Additionally, natural language models can extract key data from texts, automating evidence collection and providing quick access to up-to-date information, thereby enhancing clinical decision-making and improving patient outcomes.6 Moreover, AI tools like ChatGPT can improve scientific writing by facilitating and accelerating the creation of high-quality literature reviews and research articles. They assist in data management, error identification, and offer diverse perspectives. It is essential, however, to review and edit generated text to avoid issues, such as plagiarism.7

Yet, AI has limitations affecting its performance and accuracy. These include training data quality issues, the model's lack of common sense or intuition, vulnerability to adversarial attacks, and accountability challenges.4 Overcoming these limitations through advancements in machine reasoning, knowledge representation, and AI governance is critical as these technologies become more prevalent.

In conclusion, AI should complement, not replace, the expertise and judgement of dentists. With careful development and validation, AI has immense potential to make EBD more efficient, personalized, and proactive, significantly improving clinical decision-making and ultimately leading to enhanced treatment outcomes and greater patient satisfaction.