Data mining for Dummies - DMSK · Dummies Melanie Ganz-Benjaminsen Assistant Professor Neurobiology...

Data mining for Dummies

Melanie Ganz-Benjaminsen Assistant Professor

Neurobiology Research UnitCopenhagen University Hospital/Rigshospitalet

Department of Computer ScienceUniversity of Copenhagen

Melanie Ganz-Benjaminsen, PhD

NRU, Copenhagen University Hospital, Rigshospitalet

MSc in Physics PhD in CSPostDocin USA

PostDocat RH

Asst. Prof. at DIKU

Who am I?



Data mining

• process used to extract usable data from a larger set of “raw” data

• greatly exceeds the average data analysis you can do manually



Data science

From http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram



Machine learning

• think of machine learning as a means of building models of data

• mathematical models that help understand the data

• “learning” since there are parameters in the model that get tuned based on the available data



Machine learning

• Supervised learning:

– Classification

– Regression

• Unsupervised learning:

– Dimensionality reduction

– Clustering

• Semi-supervised learning



Classification: Predicting discrete labels



Contextualization

People who suffered a stroke

Healthy controls



Models of existing data



Prediction on new data

Categorize/make risk profiles for new patients



Too easy?

• benefit of the machine learning approach is that it can generalize to much larger datasets in many more dimensions!

• More dimensions? -> more variables e.g. gender, family history, etc.



Real example - clustering

Images taken from Beliveau et al., JNS (2017)



Real example - clustering

K = 7 K = 18

Images courtesy of Vincent Beliveau



Recap Machine learning

• is building mathematical models to help describe the relation between “input” and “output” data

– input can be age and blood pressure and output stroke status

– or input can be 5-dimensional serotonin data at ca. 10.000 vertexes of cortex and output the number of regions I want to cluster the cortical data in

• BUT mathematical models can be limited and need to be appropriate for your data



Bottom line?

High dimensional clinical and epidemiological data & statistical models with computer power

behind them (aka machine learning)

Personalized medicine ?



KU Artificial Intelligence centre

• The Data Science Laboratory (DSL) acts as the entrance for researchers and students to the AI Centre.

• Its overall aim is to enhance the quality of data analyses in research carried out at SCIENCE.



Thank for your attention!

Questions?



References

• Brown, M.S., 2014. Data mining for dummies. John Wiley & Sons

• https://jakevdp.github.io/PythonDataScienceHandbook/

• http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram

• Beliveau, V., Ganz, M., Feng, L., Ozenne, B., Højgaard, L., Fisher, P.M., Svarer, C., Greve, D.N. and Knudsen, G.M., 2017. A high-resolution in vivo atlas of the human brain's serotonin system. Journal of Neuroscience, 37(1), pp.120-128.

• Data Science lab: https://datalab.science.ku.dk/english/

https://jakevdp.github.io/PythonDataScienceHandbook/

http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram

https://datalab.science.ku.dk/english/

Data mining for Dummies - DMSK · Dummies Melanie Ganz-Benjaminsen Assistant Professor Neurobiology...

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