Metadata-Version: 2.1
Name: neuroquery
Version: 1.0.4
Summary: Meta-analysis of neuroimaging studies.
Home-page: https://github.com/neuroquery/neuroquery
Author: Jérôme Dockès
Author-email: jerome@dockes.org
Maintainer: Jérôme Dockès
Maintainer-email: jerome@dockes.org
License: BSD 3-Clause License
Keywords: neuroimaging,meta-analysis
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: dev
Provides-Extra: stemming
License-File: LICENSE

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# NeuroQuery

NeuroQuery is a tool and a statistical model for meta-analysis of the functional
neuroimaging literature.

Given a text query, it can produce a brain map of the most relevant anatomical
structures according to the current scientific literature.

It can be used through a web interface: https://neuroquery.org

Technical details and extensive validation are provided in [this paper](https://elifesciences.org/articles/53385).

This Python package permits using NeuroQuery offline or integrating it in other
applications. 

## Getting started

[Quick demo](https://nbviewer.jupyter.org/github/neuroquery/neuroquery/blob/main/examples/minimal_example.ipynb)

### Dependencies

NeuroQuery requires Python 3, numpy, scipy, scikit-learn, nilearn, pandas,
regex, lxml, and requests.

nltk is an optional dependency needed only if you use stemming or lemmatization
for tokenization of input text.

python-Levenshtein is an optional dependency used only in some parts of
tokenization. If you use the vocabulary lists provided with `neuroquery` or in
`neuroquery_data` it is not needed.

### Installation

`neuroquery` can be installed with

```
pip install neuroquery
```

### Usage

In the `examples` folder, 
[`minimal_example.ipynb`](https://nbviewer.jupyter.org/github/neuroquery/neuroquery/blob/main/examples/minimal_example.ipynb)
shows basic usage of `neuroquery`.

`neuroquery` has a function to download a trained model so that users can get
started right away:

```python
from neuroquery import fetch_neuroquery_model, NeuroQueryModel
from nilearn.plotting import view_img

encoder = NeuroQueryModel.from_data_dir(fetch_neuroquery_model())
# encoder returns a dictionary containing a brain map and more,
# see examples or documentation for details
view_img(
    encoder("Parkinson's disease")["brain_map"], threshold=3.).open_in_browser()
```

`neuroquery` also provides classes to train new models from scientific
publications' text and stereotactic peak activation coordinates (see
[`training_neuroquery.ipynb`](https://nbviewer.jupyter.org/github/neuroquery/neuroquery/blob/main/examples/training_neuroquery.ipynb)
in the examples).


BSD 3-Clause License

Copyright (c) 2023, Jérôme Dockès
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

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   this list of conditions and the following disclaimer in the documentation
   and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its
   contributors may be used to endorse or promote products derived from
   this software without specific prior written permission.

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