Data Dentistry: How Data Are Changing Clinical Care and Research.

Area of Science:

• Dental research and healthcare informatics.
• Application of artificial intelligence and big data in dentistry.

Background:

• Healthcare systems increasingly rely on data to enhance quality, accessibility, and equity.
• The dental field is evolving towards 'data dentistry,' integrating diverse data sources for improved outcomes.

Purpose of the Study:

• To outline the emerging field of data dentistry and its three primary applications.
• To identify challenges and propose action items for the dental community to advance data-driven initiatives.

Main Methods:

• Analysis of data applications in deep learning for medical data, data-enriched clinical care, and open research data.
• Identification of limitations such as data standardization, stakeholder confidence, and bias.

Main Results:

• Data dentistry leverages deep learning for data analysis, integrates multi-level data for personalized care, and promotes data sharing for research.
• Current limitations include concerns about data-driven applications, system capabilities, and lack of data standardization.

Conclusions:

• Advancing data dentistry requires increased data availability, demonstrated value of applications, workforce education, and standardized infrastructure.
• Incentivizing open data and data sharing is crucial for the successful implementation of data-driven dental innovations.