Introduction - Raniac/NEURO-LEARN GitHub Wiki

Introduction to NEURO-LEARN

NEURO-LEARN is a solution for collaborative pattern analysis of neuroimaging data. Its collaboration scheme consists of four parts: projects, data, analysis, and reports. While data preparation workflows defined in projects reduce the high dimensionality of neuroimaging data by collaborative computation, pooling of derived data and sharing of pattern analysis workflows along with generated reports on the Web enlarge the sample size and ensure the reliability and reproducibility of pattern analysis. Incorporating this scheme, NEURO-LEARN provides an easy-to-use Web application that allows users from different sites to share projects and processed data, perform pattern analysis, and obtain result reports.

Main functionalities of NEURO-LEARN was coded by Bingye Lei, who also wrote the first version of wiki. Should you encouter any problems when using NEURO-LEARN, please feel free to file an issue or contact [email protected].

The code of NEURO-LEARN is distributed under Apache License 2.0. If you find our work useful and want to publish a study using NEURO-LEARN, we would appreciate it if you cited our paper.

External Dependencies

Neuro-Learn is based on Django Web framework and Vue.js framework, which is available at https://www.djangoproject.com/ and https://cn.vuejs.org/. The feature reduction transformers and machine learning estimators are implemented with Scikit-Learn. The visualization of reports generated by NEURO-LEARN is implemented by Matplotlib.

Fast Deployment

Fast deployment of NEURO-LEARN using docker, more in NEURO-LEARN-DOCKER.