Australasian Dentist Magazine Sept-Oct 2021

Category Australasian Dentist 97 Prediction: Robots in prosthodontic interventions evolve with oral & maxillofacial surgical services. Continuum robots utilised in surgery are designed in accordance with replication of human movement and joints. A recent review1 comprehensively describes the engineering of surgical robots (mechatronics) and its applications in medicine and dentistry, and design protocols which are critical to their performance, control, safety and interactions with operators and programmers. The paper 1 identifies the Technology Readiness Level 2 of studies reviewed. It appears orthodontics, oral and maxillofacial surgery and dental education are at the frontier of getting robots into our clinics, laboratories and education providers. Prediction: High resolution optical and sectional image data via OCT- RGB scanners without ionising radiation. If you have had a photograph of your retina at your optometrist in the past ten years, you have been the beneficiary of an Optical Coherence Tomography (OCT) system. These devices acquire single-micron resolution images and can penetrate hard and soft oral structures, including dental restorations, between 2-4mm. OCTs rely on a technology known as low-coherence interferometry with near infra-red light wavelengths. Cracks, fractures, MB2, restoration voids, periodontal attachment, neurovascular bundles during surgery, amongst others, are examples of published diagnostic applications of OCT 3 . In 2020, a patent 4 was released for an intra-oral scanner which combines an OCT with an RGB scanner. A dedicated website catering to those with an interest in OCT technology currently holds over 500 publications of OCT in dental 5 . It is the opinion of the author of this article that OCT systems, such as the cited OCT-RGB scanner, will be the disruptive technology in oral diagnostic imaging over the next few years. Prediction: Neural network decision support systems will offer predictable diagnosis & treatment plans. Clinical decision support systems (CDSS) in dentistry were characterised in a 2004 review 6 . Patient interview and examination data are imported as, “Working Memory”, in the system and, with content residing in a, “Knowledge Base”, repository, analysed and diagnoses and/or treatment plans are offered at the, “User Interface”. This analysis occurs in the system’s, “Inference Engine”, which is the computational component, essentially the brain. Inference Engines may be designed in accordance with algorithmic, probabilistic, rule-based or neural network protocols. A 2018 review of artificial neural networks in dentistry 7 defined strong and weak artificial intelligence. This is highlighted with their comment regarding strong AI, “The capacity of a system that can act appropriately in an uncertain environment”. Neural networks are the design of strong AI. The concept of the Machine Learning Spectrum 8 plots the relative involvement of humans and machines in health care research and clinical care (y-axis) and the data/sample size (x-axis) for each publication. At one end of the spectrum is our traditional concept of, “Clinical Wisdom”, that being all human and no machine involvement. At the other end are neural networks with minimal human involvement, and generative adversarial networks (GANs) with no human involvement at all. GANs are essentially two neural networks (NN) in contest over a task, and the final outcome is a zero sum gain where one NN gain is the other NN loss. Commercial dental CDSS 9,10,11 are available for dental professional and business clients, including one which has been FDA-approved 9 . A large US dental laboratory and dental school published a study 12 in 2018 which used GANs for the design phase of CAD-CAM tooth-borne single crowns. It is the author’s view that strong-AI CDSS NN/GANs will predominate clinical care environments, and that weak AI-based CDSS, such as rule-based designs, will be of relevance only in dental education. Prediction: Carbon nanotube membrane technology will transform production methods of restorative materials, drug delivery and tissue engineering. Carbon nanotube membranes have emerged as a technology, “that combines and separates individual molecules to give us a ground breaking level of control over the material world … This technology has the potential to create carbon-zero gasoline, diesel, and jet fuels that are cheaper than fossil fuels by separating and combining molecules to form new raw materials.” 13 . A review 14 published earlier this year described dental applications of carbon nanotube membranes with dental restorative materials, guided bone regeneration and drug delivery. Researchers have explored the integration of glass ionomer cements with hydroxyapatite, silica and polycrystalline ceramics Alumina and Zirconia. Will we see printed ceramics one day? Next Articles: Part Two. Personalised Health, AI/ML Skills and Education Technologies Part Three. Responsible AI and Social- Ethical Infrastructure Content of these articles is derived froman invited presentation of the 2021 Scientific Meeting of The International College of Prosthodontists, “Prosthodontics 2041 – Dr Ken Hooi”. Infographic by WOW Studios For a full list of references contact gapmagazines@optusnet.com.au Prosthodontics and Dentistry 2041 This three-article series provides a brief insight into some predictions which the author believes are relevant for prosthodontics and dentistry over the next twenty years. Part One. Clinical Technologies clinical