Machine learning meets biostatistics: omics and imaging - VVSOR - VVSOR

16 May 2019

Machine learning meets biostatistics: omics and imaging

This spring the BMS-ANed and Data Science sections of the VVS-OR organise a joint meeting:

“Machine learning meets biostatistics: omics and imaging”

Date: Thursday, 16 May 2019, 12:30h – 17:30h (incl. drinks)
Location: Utrecht
Room: Aula Academiegebouw, Utrecht University


12:30 – 12:35 Welcome
12:35 – 13:25 Katrijn van Deun
13:25 – 14:15 Ernst Wit
14:15 – 14:45 Break
14:45 – 15:35 Jeroen de Ridder
15:35 – 16:25 Sach Mukherjee
16:25 – 16:30 Closing
16:30 – 17:30 Drinks


Titles and abstracts

Katrijn van Deun
Associate professor Tilburg University
Finding the hidden link: Statistical methods for multi-source high-dimensional data

Jeroen de Ridder
Associate professor UMC Utrecht
Machine learned prediction of treatment benefit in cancer

Ernst C. Wit
Professor of Data Science
Universita della Svizzera italiana
Institute of Computational Science
Statistical learning of epistasis, genetic maps and microbial networks via graphical models

Sach Mukherjee
Head, Statistics and Machine Learning,
German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
Machine learning and medicine: where do we stand and where are we going?

Registration BMS-ANed and Data Science spring 2019 meeting

Fill in the form to register for the meeting. Members of BMS, ANed, or Data Science, as well as PhD/students may join for free. Non-members who are not students pay €10,- in cash during the meeting (proof of payment will be provided). This gives access to the full programme, including the provided coffee breaks and drinks. Note that students may join BMS-ANed for free, while senior members pay the reduced fee of €27,- per year (see the Home page on how to join BMS-ANed). Note that by registering for the event, you agree to having your photo taken and possibly displayed on the BMS-ANed and/or Data Science section websites.
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    Note: you can tick BMS-ANed if you are either a member of the VVSOR section BMS, or a member of the IBS region ANed, or both.
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