Dental Data Management Using Blockchain Technology

Abstract

Biometrics” refers to identification of humans by their characteristics or traits. Dental biometrics is the technology used in forensic dentistry to identify individuals based on their dental radiographs. Dental features have proved useful for identification purposes [4]. The proposed method works with three main processing steps: [1] extraction of features by segmentation of dental works (crowns, fillings, and bridges) using mathematical morphological operations followed by thresholding; [2] generation of the dental code based on the distance between neighboring dental works and the angle at which the dental works are aligned; and [3] matching of the dental code of the panoramic radiographs with the codes in the database [4].Additionally,thesystemincorporates motion detection to address human-animal conflicts in agricultural fields. Using background subtraction and object classification (via YOLO or similar models), the system detects and classifies intruders (e.g., animals or humans) and sends real-time alerts to farm owners andofficials via Telegram notifications. Because the healthcare sector is large and ever-growing, blockchain technology offers many benefits. Researchers advocate using blockchain and smart contracts to improve dental care delivery due to their numerous advantages [3]. Blockchain ensures tamper-proof and authorized access to patient data, enabling secure interoperability between systems and facilitating seamless data exchange [2]. Patient dental and medical data, often scattered across different organizations, leads to poor care coordination; blockchain addresses this issue effectively. Efficient data management is critical in modern dentistry, ensuring the accuracy and accessibility of records for better care [1]. This paper also discusses how blockchain fits alongside other emerging technologies, promoting a digital revolution in dentistry [6].

Introduction

Dental records are vital for overall healthcare due to the strong link between oral health and systemic diseases. Traditional record-keeping methods face challenges in security and interoperability. Blockchain technology offers a secure, decentralized, and tamper-proof solution for managing sensitive dental data, ensuring data integrity, privacy, and seamless sharing across healthcare providers. Meanwhile, Machine Learning (ML) enhances dental diagnostics by automating image analysis, improving accuracy, and reducing storage needs.

The paper proposes an integrated system combining blockchain for secure dental record storage and ML for biometric identification using dental X-rays. The system encrypts and stores dental images on blockchain, extracts unique dental features for biometric matching, and uses ML models for classification. Smart contracts manage secure, patient-consented data access. Off-chain storage via IPFS handles large image files, while the frontend-backend architecture supports easy interaction for patients and clinicians.

Literature highlights successful applications of blockchain and ML in dentistry but notes challenges like scalability, regulatory issues, and limited adoption. The proposed hybrid system aims to improve privacy, interoperability, and intelligence in dental healthcare, supporting better patient care and efficient data management.

Conclusion

The system addresses the critical challenges associated with the secure storage, access control, and traceability of electronic dental records in a distributed environment. By integrating decentralized ledger technology with off-chain storage solutions, the architecture ensures data immutability, integrity, and confidentiality while supporting scalability and performance. This design facilitates a patient-centric model of healthcare data management, enabling users to retain ownership and control over their personal health information. A significant enhancement in this architecture is the integration of machine learning for automated analysis of dental radiographs. This enables the extraction of unique dental features and the generation of identifiable dental codes, which are then used for accurate patient identification and verification. The combination of blockchain’s immutability with ML-driven biometric analysis strengthens the reliability and scalability of dental healthcare systems. This approach not only secures sensitive medical data but also enhances the speed and accuracy of patient identification, supporting modern, data-driven clinical practices. Furthermore, the system supports auditability, ensuring that all access and data-related activities are permanently recorded and verifiable. In conclusion, the system combines blockchain security with machine learning-driven dental code analysis to provide a reliable and intelligent solution for securely storing dental records and accurately identifying patients, ultimately enhancing data privacy, clinical efficiency in digital dental healthcare

References

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Copyright

Copyright © 2025 Sharana Basava, Shirley Fatima S L, Sumeet Kotabagi, Vidhya Shree R, Dr. S. Andrews . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.