AI in endodontic care
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The benefits and growth of AI in Endodontics
Conversations surrounding the use and safe application of AI are inescapable. In a rapidly developing industry, news of ever improving capabilities is frequent, and publicly accessible models have put more information than ever before into the hands of clinical teams and patients.This has its benefits and its drawbacks, but safe and controlled use may be able to improve many aspects of life, including endodontic care.
As patients have access to advanced AI models, it’s also important to recognise how their use of the systems may affect clinical care interactions. Encouraging discussion is vital to ensure all involved are on the same page.
The benefits of AI in treatment planning
Healthcare systems are interacting with AI in new ways every day. Patients and clinical care teams have been able to identify definitive diagnoses, even in rare conditions, after symptoms have been presented to an AI model. This enables new conversations with the clinical care team, and further action can be taken where appropriate.
In dentistry, AI assisted imaging software is sometimes used to identify causes for concern and inform treatment approaches. In endodontics, AI may be used to support:
- Working length determination
- Periapical lesion detection
- Caries detection
- Canal system mapping
- Complex root morphology detection
Clinicians should consider the answers provided by AI as an informed second opinion, but not a sole driver of treatment approaches. Studies find that AI can be as effective as experienced clinicians for detecting periapical lesions, incidences of caries, and working length determination – but no matter the AI model used, it can never be considered flawless. Instead, the suggestions made should be double checked by the clinician to ensure patients receive the best possible care.
What can't AI replace?
The successes of AI are just one part of the story.
In many cases, they can offer unrelated or inaccurate information, or provide no additional benefit at all. A study from February 2026 found that patients who used an AI large language model (LLM) for healthcare searches were no better than a control group that didn't use the AI when assessing clinical acuity, and were worse at identifying which conditions were relevant to them.
Depending on the ways in which information is presented to an LLM, different answers may be presented. Whilst the same could be said for everyday conversations, interactions with a trained clinician allows for nuances to be picked up on, and a wider clinical network to be relied upon.
Many patients may be presenting for treatment with an AI diagnosis already in their back pocket; if this is the case, clinicians should encourage discussion. It means patients are actively engaging in their care, which can only be a good thing, but it must be supported by accurate clinical information, and confidence in the support that is available.
AI is not a solve-all solution. In endodontic care after all, whilst AI may be able to identify a problem, and suggest aspects of a treatment plan, it cannot carry out the dental care required – EndoCare, however, can. The specialist team works closely with clinicians to take on referrals in a variety of complex cases, using the latest technology and decades of experience in the field to provide leading treatment.
If you have a question about endodontic care for one of your patients, you can speak to the EndoCare team today, or use our referral form.
1. Herbert D. ChatGPT ‘uncovered woman’s rare condition’ after years of misdiagnosis. April 2026. https://www.bbc.co.uk/news/articles/cx24njzzkgjo [Accessed July 2026 Abdullah, O., Saleem, M., Hussain, Z., Mukhtiar, H., Ochani, K., Ochani, S., ... & Nur, M. A. (2025).
2. AI in endodontics: enhancing precision, efficiency, and personalized care; short communication. Annals of Medicine and Surgery, 10-1097
3. Bean, A. M., Payne, R. E., Parsons, G., Kirk, H. R., Ciro, J., Mosquera-Gómez, R., ... & Mahdi, A. (2026). Reliability of LLMs as medical assistants for the general public: a randomized preregistered study. Nature Medicine, 1-7.