Digital Support Solutions for oral health care (DSS-oral)

DSS-Oral

The shortage of resources in public oral health care challenges availability of dental care. Patients may not receive treatment in time or adequate consultation for preventive care. The project develops new AI-based tools for disease detection from images, and risk assessment to support oral health care professionals in treatment need assessment, care planning and oral health promotion.

Funders

A patient sits in a dental chair and the dentist next to her points to the underlying screen.

Project information

Project duration

-

Funded by

European Structural and Investment Funds - INTERREG

Project funder

Mid Sweden University

Funding amount

975 181 EUR

Project coordinator

University of Oulu

Contact information

Project leader

Contact person

Project description

Public oral healthcare in Scandinavia, particularly in rural and northernmost areas, faces significant challenges due to limited human resources. This scarcity results in delayed treatments of oral diseases and eventually higher treatment costs. Moreover, the lack of resources undermines efforts in preventive care, which in turn increases long-term care needs and expenses. The project is to introduce and produce tools to ease the shortage of dental care resources and to improve the availability of oral health care.

The project will develop digital support tools (DSS) for image analysis, risk assessment and preventive advice. The aim is to identify patients in need of clinical research or treatment in a more cost-effective manner and to assess the risks of oral diseases. The project produces first-hand information on both existing and developing tools for oral health professionals in the region through demonstrations and pilots.

Project actions

  • Exploration of user requirements and experiences of the use of various digital solutions (DSS) and artificial intelligence in oral health care to design and evaluate their utility.
  • Develop deep learning (DL) algorithms for image analysis to detect findings and risk factors. The work focuses on identifying teeth and detecting caries, gingivitis and plaque.
  • Develop artificial intelligence (ML) algorithms to identify the individual risk and main risk factors of oral diseases based on preliminary data collected by survey.
  • Demonstrate and pilot tool prototypes with integrated deep and machine learning algorithms developed during the project.

Project results

The expected outcomes of the project encompass the DL algorithms for dental image analysis, the ML algorithms for oral health related behavioural data analysis, the knowledge on use cases, the fit of DSS to work-flows and the desirability of the solutions.