SimulaMet research highlighted by Henrik Asheim
DeCipher aims to develop a personalized, data-driven risk assessment for cervical cancer and a framework for identifying which subgroups of patients will have similar disease progression. To do this, researchers will uncover structures hidden in existing registries and health data, and develop new machine learning methods for analysing large-scale registry and health data.
"Making cervical cancer screening more personalised is an important step in eradicating cervical cancer. Together with Simula, the Cancer Registry of Norway is collaborating to make this happen by developing algorithms and tools to be used in a real-world setting” - Jan Nygård, Cancer Registry of Norway.
In a speech at the annual meeting of the Association of Norwegian Research Institutes, the Minister of Research and Higher Education, Henrik Asheim, mentioned DeCipher as an example of how to connect research even more closely to society's needs, an important consideration in the new long-term plan for the research sector. (See the Minister's full speech here, Norwegian only).
"The Decipher project is very exciting but also scientifically challenging project as we aim to develop tools that will change the current screening practices for cervical and possibly other types of cancer. One of the most inspiring things in the project is our close and active collaboration with doctors, epidemiologists, mathematicians, and experts from the Cancer Registry Norway, we learn new things every day and hope that our tools will be deployed in real life in a short time" - senior researcher and project lead of Decipher, Valeriya Naumova.
DeCipher is a research project hosted by Simula Metropolitan Center for Digital Engineering (SimulaMet), in collaboration with the Norwegian Cancer Registry, the Norwegian University of Science and Technology (NTNU), Karolinska University Hospital (Sweden) and Lawrence Livermore National Lab (USA). SimulaMet will play a central role in the development of machine learning algorithms for longitudinal screening data analysis. (Click here for more information about the DeCipher project).