Manas Dave interviews Tuan D. Pham, Professor of Artificial Intelligence (AI) in Imaging, Diagnostics, and Trauma at Barts and The London School of Medicine and Dentistry.

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About Professor Tuan

Tuan D. Pham is Professor of Artificial Intelligence (AI) in Imaging, Diagnostics, and Trauma at Barts and The London School of Medicine and Dentistry, Queen Mary University of London, UK. He joined the UK through a prestigious Global Talent Visa, endorsed by The Royal Society for his leading work in AI and medical imaging. He also holds an Honorary Professorship at Barts Health NHS Trust, strengthening his link between academic research and clinical healthcare.

Professor Pham's research specialises in AI and machine learning for image processing, time-series analysis, complex networks, and pattern recognition, with applications spanning medicine, dentistry, biology, and mental health. He serves as an editor for several top journals and conferences and has authored three research monographs, over 160 journal articles, and more than 200 conference papers. In 2021, he was granted a US patent for a deep learning method to classify physiological signals.

His expertise earned him a role as an AI Expert for the US FDA's Network of Digital Health Experts Program, underscoring his influence in AI-driven healthcare innovation. In 2024, ScholarGPS ranked him among the top 0.05% of researchers worldwide, including #48 globally (lifetime) in Deep Learning and top rankings in Biomedical Engineering.

Professor Pham remains committed to advancing AI in healthcare and mentoring future leaders to address evolving challenges in the field.

Interview

MD: For many dental care professionals, artificial intelligence can still feel a little like science fiction. In simple terms, what is AI - and are there different types we should be aware of in the context of healthcare?

TP: Artificial intelligence, or AI, refers to the ability of computers or computerised systems to perform tasks that normally require human intelligence. This includes things like learning from data, recognising patterns, making decisions, and even understanding natural language. In dentistry, AI is already being used to assist with diagnosis, treatment planning, image interpretation, and predicting patient outcomes.

There are different types of AI that dental professionals may come across. The most common in clinical settings is what's called ‘narrow AI', which are systems designed to perform specific tasks, like detecting cavities on radiographs or predicting gum disease progression. These systems are trained on large amounts of data and become very good at one thing.

Another type of AI is ‘generative AI', which is emerging as a powerful tool in dentistry and healthcare, capable of creating new data, images, and insights that support both clinical and educational needs. In dentistry, generative AI can synthesise realistic radiographs, intraoral images, or 3D models to train students, test diagnostic algorithms, or simulate rare conditions. As generative AI becomes more sophisticated, its ability to enhance diagnosis, treatment planning, and patient communication holds great promise, provided its use is carefully validated and ethically guided.

AI in action

MD: Could you paint us a picture of how AI is already being used in dental settings or in dental education today? Perhaps an example that might surprise readers?

TP: AI is already making a quiet but powerful impact in both dental clinics and education. One example that might surprise readers, as an area of my current research in AI for oral diseases, is how AI is being used to interpret dental radiographs. Tools now exist that can automatically detect cavities, bone loss, periapical lesions, and even early signs of oral cancer on X-rays, with a level of consistency that helps reduce human error. These systems act like a second pair of eyes, offering real-time suggestions that dentists can consider alongside their own clinical judgement.

In dental education, AI is also transforming the way students learn. Virtual simulation platforms now use AI to assess a student's hand skills in procedures like crown preparations or root canals, offering immediate, personalised feedback. Some systems even track eye movements and decision-making patterns to help students develop better diagnostic skills.

Imagine a real-world clinic where, during a routine check-up, an AI system can instantly analyse intraoral photos and radiographs to assess gingival inflammation, bone levels, and plaque distribution.

One particularly exciting development is the use of AI to personalise treatment plans based on a patient's health records, lifestyle data, and even genetic information. While still emerging, this kind of precision dentistry could help tailor preventive care and interventions in ways we have never seen before.

AI at the chairside

MD: Do you see a future where AI could support tasks like periodontal screening or tracking patients' oral hygiene over time? What might that look like in a real-world clinic?

TP: Yes, we have already seen early developments that AI could play a major role in periodontal screening and long-term oral health monitoring. Imagine a real-world clinic where, during a routine check-up, an AI system can instantly analyse intraoral photos and radiographs to assess gingival inflammation, bone levels, and plaque distribution. It could flag areas of concern, like early-stage periodontitis, that might not yet be visible to the naked eye.

Beyond screening, AI could help track a patient's oral hygiene habits over time. For example, using data from smart toothbrushes or intraoral scanners, AI can monitor plaque accumulation patterns and correlate them with clinical outcomes. The system could then generate personalised hygiene reports, reminding patients (and their oral healthcare teams) where improvements are needed.

This kind of continuous, data-driven feedback loop has the potential to shift dentistry from reactive to proactive care: identifying problems before they progress and engaging patients in their own oral health with clear, objective data. In the long term, it would mean earlier interventions, fewer complex treatments, and healthier outcomes overall.

Patient conversations and compliance

MD: One challenge many of our readers face is encouraging patient compliance with oral hygiene advice. Could AI play a role in improving communication and motivation here?

TP: Yes, AI has real potential to help bridge the gap between professional advice and patient action. One of the biggest barriers to compliance is that oral hygiene advice often feels generic or abstract to patients. AI can change that by delivering highly personalised, timely feedback in a way that is easier for patients to understand and act on.

For example, as mentioned before, AI-powered apps linked to smart toothbrushes can track brushing habits and provide real-time feedback, like alerting users if they are missing certain areas or brushing too hard. Over time, these tools can show trends, celebrate improvements, and suggest small, achievable goals tailored to each individual.

AI can also enhance communication between appointments. Imagine a virtual dental assistant that checks in with patients, reminds them of hygiene goals, or answers basic questions - all based on their personal data. This consistent, supportive presence can reinforce good habits and make patients feel more connected to their care.

AI can help turn oral hygiene from a routine task into a more interactive, motivating experience to support both the patient and the clinician in achieving better outcomes.

Upskilling the whole team

MD: With technology advancing quickly, do you think understanding the basics of AI will become a core skill for dental care professionals?

TP: Yes, I strongly believe that understanding the basics of AI will absolutely become a core skill for dental care professionals. It is just like understanding infection control or radiographic interpretation. As AI tools become more integrated into diagnostics, treatment planning, and patient communication, clinicians will need to feel confident using and critically evaluating these technologies.

However, this does not mean every dental professional needs to become a data scientist, but it does mean understanding how AI systems work, what their limitations are, and how to interpret their outputs responsibly. For example, knowing whether a recommendation from AI is based on a broad dataset or a narrow one can impact how much weight we give it in clinical decision-making.

As with any new tool, the goal is to use AI to enhance, not replace, clinical judgement. And just as we once adapted to digital radiography or CAD/CAM systems, the oral healthcare team of the future will need to understand AI well enough to use it safely, effectively, and ethically. Building that knowledge now will help professionals stay ahead and continue delivering the best possible care.

Confidence through training

MD: What practical steps or resources would you suggest for a dental care professional who wants to feel more confident using or understanding AI tools?

TP: Practically speaking, for dental professionals, you do not need a background in computer science to start understanding AI and using its tools confidently. First, I recommend starting with short, accessible courses designed for healthcare professionals. Many universities and professional bodies now offer CPD-accredited modules on AI in medicine and dentistry. These cover the basics, such as how AI works, where it is used, and what questions to ask when evaluating AI tools.

Second, stay curious. Read articles or attend webinars that explore how AI is being applied in dentistry. Many articles are written specifically for clinicians and focus on practical use cases. Dentistry-focused journals often feature content on AI, digital tools, and innovation.

Finally, try hands-on exposure. Get involved if your practice or dental school is trialling an AI tool, such as software for radiograph analysis or digital workflow planning. Ask how it was trained, what kind of data it uses, and how it fits into your clinical workflow.

A glimpse into the future

MD: Looking ahead, what developments in AI excite you most when you think about the future of dentistry - and how might they change the day-to-day for the oral healthcare team?

TP: One of the most exciting developments in AI is the development toward truly personalised, predictive dentistry. In the near future, AI could integrate data from radiographs, intraoral scans, medical histories, even lifestyle and genetic information to help us identify risks/susceptibilities earlier and tailor prevention and treatment for each individual patient. Imagine being able to predict who is likely to develop periodontal disease or caries years before symptoms appear, and intervening with personalised strategies.

What excites me most is that AI can free clinicians to focus more on where they are needed most: building trust, explaining options, and caring for patients as individuals.

Another exciting area is AI-assisted clinical decision support. We will soon see AI-empowered systems that not only help detect lesions or plan implants, but also suggest treatment options based on evidence and patient-specific factors. This could streamline complex cases, reduce diagnostic variability, and support more consistent care across teams.

For the oral healthcare team, that means less time spent on repetitive tasks and more time focused on patient communication, education, and complex decision-making.

In education, AI will make training more adaptive and immersive. From virtual patients to simulation-based skill assessment, it can personalise learning for students and clinicians alike.

What excites me most is that AI can free clinicians to focus more on where they are needed most: building trust, explaining options, and caring for patients as individuals.