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Junifer and Julearn: From Neuroimaging to Machine Learning Models Without Expert-level Coding Skills

Tue, Feb 11

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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

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Junifer and Julearn: From Neuroimaging to Machine Learning Models Without Expert-level Coding Skills
Junifer and Julearn: From Neuroimaging to Machine Learning Models Without Expert-level Coding Skills

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)


Dr. Federico Raimondo
Dr. Federico Raimondo

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…


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