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Digital Frukost

Computational (bio)medicine in the age of digitalisation and super-complexity

Computational (bio)medicine aims to apply methods from engineering, mathematics, and computational sciences to improve our understanding of disease mechanisms, and diagnosis, follow-up, and treatment of human disease in the clinic. In this seminar Prof. Arvid Lundervold will talk about training of a new generation life scientists and medical students in this interdisciplinary field.

illustration Digital Frukost

Computational (bio)medicine (CM) is characterized by being multi-scale (molecule to man, microseconds to years), sub-specialized (from computational pathology to computational psychiatry), often dealing with heterogeneous, longitudinal, and high dimensional data, and addressing high-content, high-throughput data from DNA sequencers and imaging scanners as well as data from bio-banks, registers, and smartphones. CM employs an impressive range of mathematical, statistical, and computational methods, and has a tremendous potential within personalized medicine, disease prevention, and therapy.

Presently, machine learning, in particular deep learning, is dominating the field of computational medicine - progressing from fear and hype to hope. Machine learning is a core activity at the Mohn Medical Imaging and Visualization Centre (https://mmiv.no) here in Bergen.

In this talk I’ll discuss computational (bio)medicine in context of teaching and training a new generation of life scientists and medical students. The talk is partly motivated from a Nordic network of Master’s programmes in biomedicine, and the recent process of drawing up a new vision and curriculum at Karolinska Institutet - a “Biomedical Master’s program for the age of digitalisation and super-complexity” - where we have been involved.

About the seminars

"Digital Frukost" is an open breakfast seminar series focusing on research activities at the interface between the biological sciences and that of mathematics, computer science, physics or engineering. Examples of such research activities could be mathematical or computational modeling of biological systems, application of engineering/control systems theory on biological systems or inspired by biological systems, application of mathematics/statistics/machine learning to analyze big data in health or marine sector; from sensor systems, imaging or omics technologies etc.

The seminar will be at the Computational Biology Unit, Department of Informatics, UiB, 5. floor (Datablokken), Thormøhlens gate 55.

We hope to see many of you there!

As food will be served, please register your attendance using this link.