AI-Assisted, Human-Powered: Precision Periodontics
Explore how AI-powered insights combined with human expertise are revolutionizing precision, diagnostics, and personalized treatment in modern periodontics.
with Dr. Shreya Shetty
Panelists
1 expert lined up.
About this webinar
The landscape of periodontology is undergoing a radical digital transformation, driven by the rapid integration of Artificial Intelligence (AI) and Machine Learning (ML). While these technologies promise unprecedented diagnostic precision, their implementation often raises a critical question for the veteran clinician: Does the algorithm replace clinical judgment, or refine it?
Drawing on 2 decades of global academic and clinical experience, this presentation explores the transition from traditional periodontal diagnostics to an AI-assisted framework. We will examine the current state of computer vision in automated radiographic analysis—specifically the sub-millimeter detection of alveolar bone loss and subgingival calculus—and its role in reducing inter-examiner variability.
Furthermore, we will delve into the predictive power of AI in identifying perio-systemic links and identifying novel disease markers. By analyzing recent Scopus-indexed longitudinal data (2025–2026), this session evaluates how machine learning can enhance tooth-level prognosis and personalized treatment planning.
The core of this lecture argues for a "Human-Powered" philosophy. Through comparative case studies, we will demonstrate that while AI provides the data (the "What"), the clinician’s expertise is essential to provide the context (the "Why"). Attendees will leave with a clear roadmap for integrating AI into their specialty practice, ensuring that technology serves as a "navigator" while the periodontist remains the "captain."


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Date
Wed, 6 May 2026
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Time
7:30 PM IST
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CE credits
1 hours
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Content Format
Live webinar
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Access
Live + Recorded Β· Recording available afterwards
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Certificate
Issued after attendance
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Platform
Zoom Premium Platform
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Hosted by
Dentist Channel Online Intiative