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4th UZH Healthy Longevity Innovation Days - Day 2

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Datum/Zeit

June 28, 2024, from 9:00-12:00 CET

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New Address!
UZH, Seminar Room RAA-E-29
Rämistrasse 59
8001 Zürich
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Veranstalter

UZH Healthy Longevity Center and UZH Innovation Hub
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Beschreibung

The UZH Healthy Longevity Center and the UZH Innovation Hub are excited to invite you to attend the 4th UZH Healthy Longevity Innovation Days that will focus on Core Technologies for Healthy Longevity Innovation!

 

Day 2: Workshop – Explainable AI for Predicting Health Outcomes From Real-World Data

Day 2 consists of a workshop for UZH doctoral students and postdocs interested in how explainable AI can be used with real-world data for healthy longevity research and innovation. There will be a specific focus on theory and case studies to initially lay out basic principles, followed by hands-on examples to illustrate how to work with explanations.

 

8:15 – Welcome Coffee

9:00 – Overview

Prof. Dr. Mike Martin
Director, Healthy Longevity Center, University of Zurich

9:05 – Part 1: Theory and Case Studies

Prof. Dr. Janna Hastings1,2 and Dr. Charlotte Tumescheit1
1Institute for Implementation Science in Health Care, University of Zurich
2Vice-Director of the School of Medicine, University of St. Gallen

10:30 – 15 min Break

10:45 – Part 2: Hands-On Examples: Working with Explanations

Prof. Dr. Janna Hastings and Dr. Charlotte Tumescheit

11:55 – Closing Remarks

Dr. Maria Olivares
Head of Innovation, Innovation Hub, University of Zurich

12:00 – End of Day 2

 

Day 2 is reserved for UZH doctoral students and postdocs. Please do not register if that does not apply to you. Thank you!

Kurzlink: ema.uzh.ch/RV3PC

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  • Workshop – Explainable AI for Predicting Health Outcomes From Real-World Data


    UZH, Seminar Room RAA-E-29

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    Day 2 consists of a workshop for UZH doctoral students and postdocs interested in how explainable AI can be used with real-world data for healthy longevity research and innovation. There will be a specific focus on theory and case studies to initially lay out basic principles, followed by hands-on examples to illustrate how to work with explanations.

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