Getting Started - Raniac/NEURO-LEARN GitHub Wiki

NEURO-LEARN is a decentralized solution for pattern analysis of neuroimaging data. It helps neuroscientists to solve the issues of high dimension and low sample size of neuroimaging data by collaborative data and workflow sharing. (Note: the username and password for the demo page are both 'admin'.)

• Although NEURO-LEARN provides an easy-to-use platform for the pattern analysis of derived neuroimaging data, we expect you to have the basic knowledge of what machine learning techniques does and how to use them;
• The web application of NEURO-LEARN is developed and tested on a Ubuntu machine, hence we suggest you to access it via a Ubuntu machine as well. However, you are welcome to use it on a Windows machine and inform us of any problem you encounter during the usage;
• Before using NEURO-LEARN as a solution for pattern analysis of neuroimaging data, we strongly recommend you to read our paper so that you can have a general idea of what we are trying to accomplish by NEURO-LEARN.

As data are organized by projects, users can join different projects in order to upload and manage their data.

By clicking on the profile button, users can check their profile and joined projects.

As our data preparation workflows are still under development, you can refer to DPABI/DPARSF Course for the preprocessing workflows of structural/functional MRI.
Note that the format of the datasets are defined in the dataset templates, which can be downloaded from the project overview page.

Uploading a dataset is as easy as clicking a button.

For a particular machine learning task, the way to create it is submitting a task form containing the configuration of it, including task name, task type, project name, train data, label, feature selection, estimator, CV type, test data(optional), and note.

To view a report, you can click the message button on the top bar and go to the submissions overview page.

In this page, you can see the static of submitted tasks can double-click on a recent task to view its report. You can also click on 'SHOW ALL' to see all the submissions, where you can select multiple tasks and view their reports at the same time. The viewer page is where you can see the reports, and the reports provide sufficient information for you to evaluate your tasks.

Now that you are familiar with how to use the web app provided by NEURO-LEARN, the next step would be reading the reference and grasp the full functionality of it.