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4th Clinic meets Data Science Symposium

Clinical Data Science focuses on developing computational software and databases. Enhanced digitalization and data volume at hospitals has increased the demand for Data Science in the clinics to empower data-driven precision medicine. Our symposium will showcase these efforts, highlight current and future applications and developments in Clinical Data Science and discuss possibilities and opportunities that Data Science offers for the clinical daily routine.

Location

Hybrid Event

University Hospital Zurich
Grosser Hörsaal OST
Schmelzbergstrasse 12
8091 Zürich

Date

10.09.2024

Time

9.00 a.m. - 6.00 p.m.

Credits

tbd

Costs

No conference fee

Program

9.00 a.m. Welcome
Session 1: Chair: Michael Krauthammer
9.10 a.m. Keynote: Data Science in a Swiss Public Hospital: Challenges and Opportunities
Ruinelli Lorenzo, Ente Ospedaliero Cantonale
9.50 a.m. Early and Personalized Antifungal Resistance Prediction Based on Machine Learning Approaches
Yiqi Yang, ETH Zurich
10.20 a.m. LLM-based management of common data elements along the care path of breast cancer patients: The SMARAGD project

Fabio Dennstädt, Inselspital Bern
10.50 a.m. Break + Poster
11.20 a.m. Prospective and External evaluation of an AI model for continuous and early prediction of moderate and severe AKI in critically ill patients

Simone Zappalà, U-Care Medical Srl
11.50 a.m. Keynote: All that glitter is not gold: tales of using deep learning for clinical data

Chloé-Agathe Azencott, Mines Paris–PSL, Institut Curie and INSERM
12.30 p.m. Lunch Break
1.40 p.m. Keynote: The anatomy of a model: Interrogating language model capabilities and risks for medicine

Danielle Bitterman, Harvard Medical School
2.20 p.m. Physiological Complexity Approach to early detection of disorders in Neurophysiology and Computational Psychiatry

Milena Cukic Radenkovic, University in Rapperswil-Jona
2.50 p.m. Early identification of ventilator-associated pneumonia using machine learning techniques: a prospective cohort study.

Alberto Pagnamenta, Ruinelli Lorenzo, Ente Ospedaliero Cantonale
3.20 p.m. Break + Poster
3.50 p.m. FPLIER: A Federated Learning Method for Transcriptomics

Daniele Malpetti, University of Applied Sciences of Southern Switzerland
4.20 p.m. Data-Driven Phenotype Analysis: A Pipeline for Structured Extraction of Clinical Information from Patient Reports

Daphné Chopard, University Children’s Hospital Zurich
4.50 p.m. Keynote: Knowledge-based machine learning  to find disease mechanisms from multi-omics data
Julio Saez-Rodriguez, University Hospital Heidelberg
5.30 p.m. Panel Discussion: Future Challenges of Data Science in Clinics
Chairs: Beatrice Zanchi, Charlotte Tumescheit, Diane Duroux, Zsolt Balazs
6.00 p.m. End + Apéro
Access Zoom

Registration

Scientific Organizing Committee:
Beatrice Zanchi
Charlotte Tumescheit
Diane Duroux
Zsolt Balázs

Program chair members:
Janna Hastings
Vice-Director of School of Medicine, University of St. Gallen
Michael Krauthammer
Director of Department of Quantitative Biomedicine, University of Zurich
Francesca D. Faraci
Group leader, University of Applied Sciences and Arts of Southern Switzerland
Abdullah Kahraman
Group Leader, University of Applied Sciences Northwestern Switzerland

Responsible Department

Comprehensive Cancer Center Zurich