NeuroMiner#
Manual for NeuroMiner Version 1.3#
Software written by Nikolaos Koutsouleris, Clara Vetter & Ariane Wiegand
Version release date: 24th September 2024
How to cite NeuroMiner#
Koutsouleris, N., Vetter, C., Wiegand, A., Hahn, L., & Mena, S. (2024). NeuroMiner (Version 1.3). GitHub. neurominer-git/NeuroMiner_1.3
Machine learning for precision psychiatry#
Machine learning techniques are poised to become clinically useful methods that may be used for diagnosis, prognosis, and treatment decisions. Despite this, they are currently underutilised in medical studies, and moreso in psychiatric research because most current tools require strong programming and computational engineering skills (e.g., scikit-learn, caret, Weka, nilearn). While there are some great tools that do not require programming experience (e.g., PRoNTo), these tools are often limited to making predictions from domain-specific modalities such as neuroimaging data. This highlights a pressing need for a user-friendly machine learning software that makes advanced methods available to clinical researchers from different fields, aiming at collaboratively developing diagnostic, predictive, and prognostic tools for precision medicine approaches.
Check out the manual and tutorials to get started!
News
Getting started
NeuroMiner interface
- Main interface overview
- Data entry in NeuroMiner
- Define parameter template
- Initialize analyses
- Preprocess features
- Train supervised classifiers
- Visualize classifiers
- Interprete predictions
- Result Viewer
- Out of Sample Cross-Validation
- Export model parameters
- Load NeuroMiner structure
- Save NeuroMiner structure
- Change working directory
- Estimate sample size (simulation tool)
- Utilities
Parallelization
Examples