POSTPONED - Big Data & - Artificial Intelligence
The course is expected to be held in 2021.
Due to the enhanced situation with the COVID-19, several Danish hospitals and universities have tightened up their rules regarding travel and participation in both national and international conferences and meetings. Therefore, we have decided to follow their decision and postpone the course.
More information regarding the exact dates for the course will follow. Please stay updated on our website.
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The amount and complexity of data is increasing enormously today and in the years to come and there is a need to prepare how we handle diverse types of data to interpret disease and treatment responses.
This event will bring together world-class experts in the fields of health-related data integration and artificial intelligence as well as diabetes leaders with data science showcases. Participants will have active or near-term data-focused projects to create and engage in discussions.
- Time & place
- Who can attend?
- Detailed description
- Programme & speakers
- Organisers
- Registration
- Additional information
TIME & PLACE
TBD
WHO CAN ATTEND?
The workshop is targeted at PhD students and postdocs in the field of diabetes and other health areas, with a strong active interest and knowledge in complex data integration, as well as Big Data and Artificial Intelligence.
Due to the limited number of seats on the workshop, you are not guaranteed a seat until you receive an e-mail with final confirmation. You will thus initially be placed on a waiting list, which will be prioritized according to your submitted abstract and CV.
DETAILED DESCRIPTION
This workshop aims to highlight the state-of-the-art data methodologies in diabetes and other health areas within Big Data and Artificial Intelligence and explore the strengths and limitations of using machine learning methodologies on complex diseases. In addition the workshop will focus on how data can contribute to molecular understanding of diseases; the diversity of methods used when working with data integration & artificial and gives the opportunity to the participants to have an idea on how their own methods relate to global efforts, and expand their horizon and network.
Learning objectives:
To be able to reach the aim of the workshop, the participants must:
- Actively participate during the event: present and discuss their own work
- List ideas of how to improve their own methods based on inspiration from others working with data
- Identify diverse methods for working with Big Data & Artificial Intelligence
- Be able to explain the importance, strengths and limitations of machine learning
- Be able to address how to handle large and difficult data sets
- Be able to explain how to derive value from small data sets
- Elucidate ideas for how data from health records can be integrated
PROGRAMME & SPEAKERS
Confirmed speakers:
- Professor Marylyn D. Ritchie, Director, Center for Translational Bioinformatics, Institute for Biomedical Informatics (IBI) University of Pennsylvania (US)
- Professor Paul Franks, Lund University Diabetes Centre, (S)
- Dr. Anna Bauer-Mehren, Head Data Science Roche Innovation Center Munich - Pharma Research and Early Development (D)
- Professor Jose Florez, Harvard Medical School & Chief of The Endocrine Division and Diabetes Unit at the Massachusetts General Hospital (US)
- Head of data and knowledge management, Alexander Jarasch, German Center for Diabetes Research (D)
- Product Director Ketan Patel, Clarivate Analytics (UK)
- Associate Professor Casey Greene, Systems Pharmacology and Translational Therapeutics in the Perelman School of Medicine at the University of Pennsylvania (US)
- Head of Applied AI Architecture Laurent Gautier, Sanofi Aventis
- Postdoctoral Research Fellow Tejaswini Mishra, Stanford University School of Medicine (US)
- Associate Professor Ramneek Gupta, Technical University of Denmark
- CEO and co-founder Emil Eifrem, Neo4j, Inc
ORGANISERS
- Danish Diabetes Academy (DDA, DK)
- German Center for Diabetes Research (DZD, DE)
- Associate Professor Ramneek Gupta, Technical University of Denmark (DK)
- Head of data and knowledge management Alexander Jarasch, German Center for Diabetes Research (DE)
- Professor Paul Franks, Lund University Diabetes Centre, (SE)
REGISTRATION
Registration deadline: March 16, 2020 (midnight)
You must submit an abstract and CV when you register.
Abstract:
Word format of up of maximum 500 words when registering following this information
Presenting author name, author name, author name
- Affiliation: Name and address of workplace,
- Background and aim
- Material and methods
- Results
- Conclusion (and perspectives)
Curriculum Vitae:
Please attach a CV/resume of max 2 A4 pages
ADDITIONAL INFORMATION
Dinner registration
There will be a networking dinner on 31 March and 1 April. Please state if you will participate in the dinner when you register.
Accommodation
For participants living outside Copenhagen it is possible to get accommodation at WakeUp, Copenhagen. Please state if you would like accommodation when you register.
Certification
A course certificate will be handed out to all PhD students on request at the end of the course. Full participation is required to attain ECTS point. ECTS points: TBA
No-show fee
Please note that it is free of charge to participate in the course however the DDA will charge a no-show fee of 500 DKK if you have not unregistered from the course prior to course start.
Poster:
If you are selected for participation, you are expected to present your data at a poster session. Please use the below listed guidelines:
Size of poster: A0 or A1 - width max. 1 m/height max. 1.25 m
When your abstract has been accepted, your poster will be assigned a number in the abstract book. You will find the corresponding number at the poster stands on which your poster should be placed.
Pins will be available at the poster stand.
For inspiration, please visit https://www.posterpresentations.com/free-poster-templates.html