Digital support solutions for oral health care (DSS‑oral)

Access to dental care is a challenge in rural areas, where a lack of staff and resources makes preventive care difficult and leads to increased costs. Through AI-based image analysis and machine learning, this project aims to contribute to making dental care more efficient and improving oral health.

Närbild tandläkare sjuksköterska håller tablett med digitala tandbilder

The project addresses the shortage of dental care resources in the Aurora region and strives for improved access to oral healthcare. Public oral healthcare in Scandinavia, particularly in rural and northernmost areas, faces significant challenges due to limited human resources, but the challenges also exist in other areas. 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. On the other hand, regions like Västernorrland County and Oulu Region, known for their proficiency in digitalization, offer fertile ground for innovation in digital healthcare solutions.

The goal is to develop Digital Support Solutions (DSS) for image analysis, risk assessment and preventative counselling that support identifying patients needing clinical examination or treatment and identify risks. The aim is let the regions oral healthcare professionals get first-hand experience of DSS tools.

The key actions of the project are: (i) Collecting information of use cases and users experiences and expectations regarding DSS. (ii) Implementing and evaluation of deep learning and machine learning algorithms to detect teeth, caries, gingivitis and plaque from dental images. (iii) Implementing and evaluation of ML algorithms and data preprocessing to predict risk detect caries and gingivitis risk levels(iv) Deploying explainable AI methods to identify the disease risk factors and to facilitate preventive counselling messaging. (v) Demonstrating and piloting the developed DSS to obtain information on their solution fit, user desirability, functionality and safety.

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.