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No Code AI - with Spinoza Professor Mihaela van der Schaar (Cambridge)

Foto van Mark Hoogendoorn
Hosted By
Mark H. en Paul E.
No Code AI  - with Spinoza Professor Mihaela van der Schaar (Cambridge)

Details

As a follow up to the appointment of Mihaela van der Schaar as Spinoza Guest professor we are excited to announce a special tutorial session exclusively for Amsterdam Medical Data Science members and Amsterdam UMC students and faculty on CliMB-DC, an advanced co-pilot designed to enhance data-driven decision-making in machine learning.

Date: 22 April
Time: 13:00 – 15:00 (Amsterdam Time)
Location: Online

CliMB-DC (Clinical Machine learning Builder – Data Centric) is an AI-enabled partner designed to empower clinician scientists to create predictive models from real-world clinical data, all within a single conversation. With its no-code, natural language interface, CliMB-DC guides you through the entire data science pipeline, from data exploration and engineering to model building and interpretation. The intuitive interface combines an interactive chat with a dashboard that displays project progress, data transformations, and visualisations, making it easy to follow along. Leveraging state-of-the-art methods in AutoML, data-centric AI, and interpretability tools, CliMB-DC offers a streamlined solution for developing robust, clinically relevant predictive models.

Key Highlights of the Tutorial:

  • Overview of CliMB-DC and its capabilities for data-centric decision making
  • Practical demonstration of how to use the framework for your tasks
  • Q&A session with our experts to address your specific questions
  • Presenters: Prof Mihaela van der Schaar, Dr Anders Boyd, Evgeny Saveliev
  • This tutorial will be valuable for anyone looking to elevate their data-centric research in machine learning, particularly those in healthcare-related studies.
Photo of Amsterdam Medical Data Science (AMDS) group
Amsterdam Medical Data Science (AMDS)
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