Arvid Lundervold: Computational Medicine and Machine Learning - Opportunities and Challenges Arvid Lundervold: Computational Medicine and Machine Learning - Opportunities and Challenges The Delft Data Science Seminar: Visual Data Science and its role in Computational Medicine - February 6th 2018 COMPUTATIONAL MEDICINE and MACHINE LEARNING - Opportunities and Challenges Arvid Lundervold BSc, MD, PhD Neuroinformatics and Image Analysis Laboratory Neural Networks Research Group Department of Biomedicine, University of Bergen, Norway & Mohn Medical Imaging and Visualization Centre, Haukeland University Hospital (in collaboration with Assoc Prof Alexander S. Lundervold) www.uib.no|arvidl.github.io|mmiv.no
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Arvid Lundervold - Visualization · Arvid Lundervold: Computational Medicine and Machine Learning - Opportunities and Challenges • “Applying methods from engineering, mathematics
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Arvid Lundervold: Computational Medicine and Machine Learning - Opportunities and Challenges Arvid Lundervold: Computational Medicine and Machine Learning - Opportunities and Challenges
The Delft Data Science Seminar: Visual Data Science and its role in Computational Medicine - February 6th 2018
COMPUTATIONAL MEDICINE and MACHINE LEARNING
- Opportunities and Challenges
Arvid Lundervold BSc, MD, PhD
Neuroinformatics and Image Analysis Laboratory Neural Networks Research Group
Department of Biomedicine, University of Bergen, Norway & Mohn Medical Imaging and Visualization Centre, Haukeland University Hospital
(in collaboration with Assoc Prof Alexander S. Lundervold)
Arvid Lundervold: Computational Medicine and Machine Learning - Opportunities and Challenges Arvid Lundervold: Computational Medicine and Machine Learning - Opportunities and Challenges
• “Applying methods from engineering, mathematics and computational sciences to improve our understanding and treatment of human diseases”
– Rai Winslow, Director, Institute for Computational Medicine, Johns Hopkins University
• “A new field of science, which embraces mathematics, physics, information technology, biomedical engineering and medicine ... ... to collect, manage, mine, analyse and visualise a very heterogeneous mixture of datalike personalised genetic and proteomic profiles, bio-signals and the monitoring ofmovement, advanced imaging, and other relevant phenotype information in such a way that useful clinical information for improving human health can beextracted.”
– M. Daumer, SLCMSR / Munich&Cambridge International School for Clinical Bioinformatics and Technical Medicine
Similar terms: Systems medicine, computational health informatics
What is “computational medicine” ?
Arvid Lundervold: Computational Medicine and Machine Learning - Opportunities and Challenges Arvid Lundervold: Computational Medicine and Machine Learning - Opportunities and Challenges
The paradigm shift in cell and molecular biology
- from a reductionist approach to an integrative approach
B. O. Palsson, Systems biology: Properties of reconstructed networks, Cambridge University Press, 2006
Quantitative imaging & modelling
/ Systems
medicine
Arvid Lundervold: Computational Medicine and Machine Learning - Opportunities and Challenges Arvid Lundervold: Computational Medicine and Machine Learning - Opportunities and Challenges
Medicine and the “new” computational fields
Data Science `producing insights’ e.g. explorative and longitudinal data analysis
Machine Learning `producing predictions’ e.g. biomarkers treatment response
Artificial Intelligence `producing actions’ e.g. imaging-guided robot surgery
Arvid Lundervold: Computational Medicine and Machine Learning - Opportunities and Challenges Arvid Lundervold: Computational Medicine and Machine Learning - Opportunities and Challenges