Data Science Techniques for Datasets on Mental and Neurodegenerative Disorders

(DS Techniques for Datasets on MDs and NDs)

The burden of mental and neurodegenerative disorders (MDs and NDs) is estimated to grow to $6 trillion by 2030. Artificial intelligence techniques can make detection and treatment of these disorders easier, promising improved treatment and patient outcomes. However, developing trustworthy AI models and integrating them into healthcare settings, especially with such vulnerable populations, requires advanced data science techniques. 

The DS Techniques for Datasets on MDs and NDs workshop will provide a comprehensive discussion of data science techniques for biomedical datasets related to mental and neurodegenerative disorders. The goal of this workshop is to allow mental health researchers to expand their knowledge of advanced data science techniques while enabling data scientists to improve their methods with feedback from clinical audiences.

22 June 2023

13:00 - 16:00 CEST

JED Zurich (Zürcherstrasse 39, 8952 Schlieren)  


Mah Parsa

Computer Research Institute of Montreal

Lauren Erdman

SickKids, University of Toronto

Vector Institute



Dr. Giulia Da Poian 

From Data Streams to Precision Outcomes:

Expanding Mental Health Research with Data Science and Passive Sensor Data 

Invited Speaker: 

Dr. Sarah Brüningk

Harnessing clinical hallmarks for Alzheimer’s Disease detection on MRIs 

Lightening Talk

Jenny Yu

Maternal Childhood Adversity’s Impact on Dynamic Mental Health During Pregnancy:

A Causal Approach