Data sharing for responsible artificial intelligence in dentistry: a narrative review of legal frameworks and privacy-preserving techniques

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11110%2F25%3A10505787" target="_blank" >RIV/00216208:11110/25:10505787 - isvavai.cz</a>

Result on the web

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=vp2aMwse7H" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=vp2aMwse7H</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jdent.2025.106130" target="_blank" >10.1016/j.jdent.2025.106130</a>

Result language

angličtina

Original language name

Data sharing for responsible artificial intelligence in dentistry: a narrative review of legal frameworks and privacy-preserving techniques

Original language description

Objectives: Data sharing is essential for ensuring research reproducibility and for developing generalizable artificial intelligence (AI) systems, but it demands robust safeguards for patient privacy. This narrative review aims to guide dental clinicians and researchers in sharing patient data responsibly while preserving confidentiality. Data: Dental patient data include radiographs, (cone beam) CTs, photographs, intraoral scans, tabular data, and electronic health records. These datasets are often heterogeneous, distributed across institutions, and subject to strict privacy regulations. Handling and sharing such sensitive data requires secure, privacy-preserving techniques to ensure compliance with legal and ethical standards. Sources: PubMed, Embase, Scopus, arXiv and Google Scholar were searched using keywords related to dentistry, data sharing, AI, and privacy-preserving techniques. Given the limited number of results relevant to dentistry, the search was extended to medicine. In parallel, we reviewed applicable regulatory frameworks such as the European Union (EU) General Data Protection Regulation (GDPR), Health Insurance Portability and Accountability Act (HIPAA), EU AI Act, and European Health Data Space (EHDS). Study Selection: We selected studies addressing data sharing in dentistry/medicine, de-identification, privacy-preserving techniques, and/or federated learning, as well as applicable regulatory frameworks. Most of the articles were peer-reviewed, but authoritative grey literature was included as well. Conclusions: This review summarized legal and technical aspects of dental data sharing to enable compliant multi-institutional collaboration. Beyond AI in dentistry, which was primarily emphasized, responsible data sharing is integral to FAIR practice and strengthens transparency and reproducibility across dental and medical research. Clinical significance: This review provides regulation-aligned guidance on de-identifying and sharing dental data, enabling compliant multi-institutional collaboration while protecting privacy. By promoting responsible AI development and reproducible research, it translates into more reliable care and greater patient trust in everyday clinical practice.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

30208 - Dentistry, oral surgery and medicine

Project

—

Continuities

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of Dentistry

ISSN

0300-5712

e-ISSN

1879-176X

Volume of the periodical

163

Issue of the periodical within the volume

December

Country of publishing house

GB - UNITED KINGDOM

Number of pages

9

Pages from-to

106130

UT code for WoS article

001613974600002

EID of the result in the Scopus database

2-s2.0-105020713206