MUMBAI, India, June 26 -- Intellectual Property India has published a patent application (202621051102 A) filed by Ganesh Deshmukh on April 22, 2026, for System And Method For Early Malocclusion Detection Using Ai- Driven Dermatoglyphic Analysis And Habit-Based Decision Trees.
Inventors include Dr. Ramchandra Pujari; Ganesh Deshmukh; and Dr. Mohit Kumar.
The application for the patent was published on June 19, 2026, under issue no. 25/2026.
Abstract: The current research says there is a statistical association between fingerprints and skeletal Malocclusions. There is no AI present to predict the malocclusion based on hybrid techniques involving fingerprints. The present invention relates to a system and method for the early detection and prediction of malocclusion risk using dermatoglyphic analysis and Habit-Based Decision Trees integrated with artificial intelligence (AI). The system comprises a dermatoglyphic scanning module for capturing fingerprint patterns, a data input module for recording oral habits such as thumb sucking and pacifier use, and an AI-driven analysis module using CNN and ensemble techniques. trained to identify correlations between dermatoglyphic features and skeletal malocclusion. A decision tree processing module refines predictive accuracy by incorporating behavioral habit data, while a classification module assigns individualized malocclusion risk levels based on combined dermatoglyphic, clinical, and behavioral parameters. The system further includes a recommendation module that generates predictive reports with preventive and interceptive orthodontic guidance, supported by a cloud-based infrastructure for data storage, continuous learning, and model optimization. The invention also discloses a method for preprocessing dermatoglyphic data, applying machine learning-based pattern recognition, and generating risk scores through integrated analysis. Additionally, a mobile application platform enables accessible, large-scale screening, real-time diagnostics, and teleconsultation support, making the solution particularly suitable for mass screening in underserved populations. Overall, the invention provides a non-invasive, scalable, and AI-enhanced approach for early orthodontic risk assessment, improving preventive care outcomes through timely intervention and data-driven decision-making.
Disclaimer: Curated by HT Syndication.
