WIML: Workflow-integrated machine learning

Recent years have seen exciting applications of machine learning in medical data analysis, from radiology and dermatology to electronic health records and drug discovery. This has led to great interest and enormous expectations from the medical profession. However, it is still early days for the evaluation and integration of artificial intelligence and machine learning-derived information in clinical practice. This proposal addresses one of the crucial missing elements required for implementation and integration in clinical radiology: an innovative, direct integration of computational imaging methods with picture archive and communication systems (PACS). To ensure the usefulness of our innovation, we apply and evaluate the system on multiple important health challenges.

The project is financed by the Norwegian Research Council, #309755, 7MMNOK.

See https://mmiv.no/wiml for further details about the project.

Samarbeidspartnere

Mohn Medical Imaging and Visualization Center, Helse Bergen HF, Universitetet i Bergen, Høgskulen på Vestlandet

Formål

The project's main objective is to design and develop a "Research Information System" in the Western Norway Regional Health Authorities (Helse Vest RHF) that integrates a data model for images and tabular data with computations in the form of statistical and machine learning models.

Ekstern lenke til prosjektet

https://mmiv.no/wiml