The ASReview Users Meeting aims to bring together people who use or contribute to one of the many subprojects within the ASReview universe. The goal is to meet each other, share information, learn about new developments and discuss collaborations.
ASReview Users Meeting
The meeting is free, but organizing it is not. To facilitate catering (coffee, tea, etc) and to arrange the administration, we ask participants for a donation via the university’s crowdfunding platform.
Who, When, Where?
Who?
Anybody can participate; whether you have brilliant ideas, love statistics (or not!), or want to listen to the great adventures in the ASReview-universe, you are very welcome! It is all about learning and improving your skills. You can also meet new people who can introduce you to incredible new insights or ways of working. You might meet your next co-author, funder, or best-Elas-buddy.
Because we want to stimulate interaction and collaboration, the maximum number of participants is ~30.
When?
Thursday, March 23 (2023) – 9.00-12.30 (CET) with the option to stay and collaborate/contribute
2023/03/23 09:00:00
Where?
ASReview Community Room – Located in the old University Library – Entrance at the Drift 27 – Room 0.21 – Utrecht, The Netherlands.
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Program
Confirmed speakers
Session 1
Mining Argument from Text with MARGOT – By Elisa Ancarani (student, University of Bologna; ASReview intern)
HOLM: Hyperparameter Optimization to accelerate active Learning Models – By Ayoub Bagheri (ASReview team)
Handcrafting Searches for AI-Aided Systematic Reviewing – By Felix Weijdema (information specialist at Utrecht University library)
Using AI (ASReview) to detect psychological themes in adolescent narratives – By Jaap Denissen (Dynamics of Youth)
Session 2
Current state of affairs of the AI-aided knowledge discovery lab – By Matthieu Brinkhuis (Associate Professor, Utrecht University) and Rens van de Schoot (ASReview team)
Determining the impact of ASReview within health economic papers – By Martijn Oude Wolcherink (PhD candidate, University of Twente)
Towards a copyright-respecting systematic review database for machine learning – By Jonathan de Bruin (ASReview team)