Nilearn is a Python module for fast and easy statistical learning on NeuroImaging data that leverages the scikit-learn Python toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis.
Customer Reviews
Paresh A.
Advanced user of NilearnNilearn is the machine learning library developed especially for the neuroimaging data processing.It has vast trained models on the neuro imaging data gathered from various MRI machines and other neuro imaging machines.It can be used to apply supervised learning on neuroimaging data as well it can be used to suggest the treatment in accordance with the input data to predict the treatment.It can also be used for Decoding and MVPA.So it is the best library for applying Machine Learning on neuroimaging data and predict proper results.
I have nothing to dislike about Nilearn because it has given best results for my application.
I recommend using Nilearn because it helps you to predict best results on neuroimaging data and works better than any other API's so I would suggest using Nilearn if you are dealing with neuroimaging data or doing research on applying ML on neuroimaging data.Also if you are working to develop software for health sector dealing with neuro science than you should use Nilearn.In short if you are dealing with neuroimaging data I recommend you using Nilearn.
I am a software developer and have to work with various sectors and develop softwares for them so I also get projects from health sector and for that I have to develop software for neurological doctor to predict the treatment in accordance with the imaging results and at that time I used Nilearn for the project.I also used it once for developing software for MRI developing company to integrate it with their machine.So Nilearn has helped us a lot.
