Junifer and Julearn: From Neuroimaging to Machine Learning Models Without Expert-level Coding Skills
Tue, Feb 11
|Virtual Event
This presentation covers the following points: 1. When and how to design analysis to uncover brain-behaviour associations using Machine Learning 2. How to easily extract relevant information from neuroimaging using Junifer 3. How to build and evaluate Machine Learning models with Julearn
Time & Location
Feb 11, 2025, 8:30 a.m. – 9:30 a.m. PST
Virtual Event
Guests
About the event
Topic: Junifer and Julearn: From Neuroimaging to Machine Learning Models Without Expert-level Coding Skills
Time: Febrary 11, 2025 8:30AM PST / Febrary 11, 2025 11:30AM EST / Febrary 11, 2025 17:30PM CET / Febrary 12, 2025 00:30AM CST (timezones)
The detailed Zoom meeting information will be provided in the email upon completion of your registration with your email address.
Speaker: Federico Raimondo (Team Leader at Institute of Neuroscience and Medicine [INM-7: Brain and Behaviour], Research Centre Jülich, Jülich, Germany)
Thanks to big data and computational power, the study of brain-cognition relationships using neuroimaging and machine learning (ML) has gained significant popularity [1]. Importantly, decisions in data processing [2] and predictive modelling [3] strongly impact the results. Also, misconceptions about ML procedures can distort or even invalidate findings [4], hence escalating the neuroimaging reproducibility crisis [5]. These decisions and implementations can become increasingly complex, posing challenges for early-career researchers: they require proficiency in diverse skills to deal with large-scale datasets, algorithms, and complex…