CATEGORY 102 AUSTRALASIAN DENTIST ARTIFICIAL INTELLIGENCE Dentistry has come a long way in a short time. Over the past two decades, the profession has made a remarkable transition, from lm-based radiographs to digital sensors, from paper charts to practice management software, from physical impressions to intraoral scanners. ese advances have been genuinely transformative. ey have made dental practice faster, cleaner, and more connected. But here is the uncomfortable truth: digital alone has not made us more accurate. e image is crisper. e work ow is faster. Yet the fundamental act of diagnosis, a trained clinician examining a radiograph under time pressure, patternmatching across dozens of subtle greyscale variations remains largely unchanged. We have digitised the capture of data without fundamentally improving how we interpret it. Digital transformed how dentistry captures data. Intelligent systems are transforming what we do with it. at is the gap this article is about. And it is a gap that the profession can no longer a ord to ignore. The limits of digital Ask any clinician how many radiographs they review in a day and the answer is often in the dozens. Each one demands focused attention. Each one carries clinical stakes. And each one is assessed by a human mind that, however skilled and well-intentioned, is subject to fatigue, cognitive load, and the natural variability that comes with being human. Research consistently shows signi cant inter-examiner and intraexaminer variability in dental radiograph interpretation. Studies of caries detection, periodontal bone loss assessment, and periapical lesion identi cation all point to the same nding: two clinicians examining the same image will frequently reach di erent conclusions. e same clinician, Dentistry is becoming intelligent: What comes after digital? By Khoa Le and Dr Sen Le examining the same image on di erent days, may reach di erent conclusions. is is not a criticism of the profession. It is an acknowledgment of the limits of human perception when applied to highvolume, high-stakes visual interpretation tasks. ese are precisely the conditions where machine intelligence can add the most value. Enter intelligent dentistry e concept of intelligent dentistry builds on the digital foundation the profession has already established. It does not replace the clinician, it augments them. Where digital systems capture and store information, intelligent systems analyse and interpret it. Where digital tools streamline work ow, intelligent tools actively reduce variability and improve diagnostic consistency. At its core, intelligent dentistry means using arti cial intelligence to assist in clinical decision making. In practical terms, this looks like AI that analyses a bitewing radiograph and ags potential caries. It looks like a system that reviews a full-mouth series and highlights regions of concern across multiple teeth simultaneously. It looks like software that tracks bone levels over time and alerts the clinician to Dr Sen Le Khoa Le Key insight: Variability in diagnosis is not a failure of skill – it is an inherent feature of unaided human perception under clinical pressure. Intelligent systems are designed to address exactly this.
RkJQdWJsaXNoZXIy MTc3NDk3Mw==