Hands on with nilearn for brain imaging (en)
This is an introductory level talk on nilearn which is an open-source Python package to help in faster and easy learning of brain MRI images. The talk aims to introduce attendees to Neuroimaging and nilearn and how Machine Learning can help in Neuroimaging.
The talk aims to introduce audience to Neuroimaging and how Machine Learning can help neuroscientists make informed decisions on brain MRI scans and also learn more on the features offered by nilearn which can help neuroscientists in the data analysis.
The nilearn makes use of scikit-learn Python Toolbox used for machine learning and improves over it by adding new applications such as predictive modelling,analyzing connectivity,decoding. Nilearn as a package,helps make Machine Learning relevant to the field of Neuroimaging and helps in answering questions like predicting treatment responses for a person with autism or Parkinson’s disease. This talk will focus on Nilearn,How it improves upon scikit-learn and how it helps neuroscientists to make imformed decisions about brain images.The talk aims to introduce attendees to Neuroimaging and nilearn and how Machine Learning can help in Neuroimaging.