We are developing research methods for cancer and cancer screening and investing in efficient analysis methods.
We are studying the statistical properties of cancer burden indicators and developing versatile reality-mimicking simulation models for evaluating cancer screenings. We are expanding the knowledge base through text mining and studying the use of artificial intelligence in processing large amounts of data.
The project creates statistical model-based tools for evaluating the colorectal cancer screening programme. The models are used to build simulations based on which, for example, the significance of screening interval, different tests, risk group-based screening, and screening age groups in the effectiveness of the programme can be studied. The project has developed a simulation model based on Finnish individual-level data, and tools for modelling risk-based screening and evaluating the screening programme are currently being developed.
The research project is developing a statistical model for estimating future colonoscopy capacity needs in the colorectal cancer screening programme. The model takes into account the number of screening rounds for those invited to screening, trends in participation activity, and regional population structure. Additionally, the volume of colonoscopy activities is being modelled by region, aiming to produce more real-time information on the development of the colonoscopy queue situation.