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|
%global _empty_manifest_terminate_build 0
Name: python-deduce
Version: 2.0.3
Release: 1
Summary: Deduce: de-identification method for Dutch medical text
License: LGPL-3.0-or-later
URL: https://github.com/vmenger/deduce/
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/f6/4a/d79ce593caaa7cefe098c84c0116f7e82017d3ab3c54cf2e6434bd3d457b/deduce-2.0.3.tar.gz
BuildArch: noarch
Requires: python3-rapidfuzz
Requires: python3-docdeid
Requires: python3-regex
Requires: python3-deprecated
%description
# deduce
[](https://github.com/vmenger/deduce/actions/workflows/test.yml)
[](https://coveralls.io/github/vmenger/deduce?branch=master)
[](https://github.com/vmenger/deduce/actions/workflows/build.yml)
[](https://deduce.readthedocs.io/en/latest/?badge=latest)
[](https://github.com/psf/black)
[Installation](#installation) - [Versions](#versions) - [Getting Started](#getting-started) - [Documentation](#documentation) - [Contributiong](#contributing) - [Authors](#authors) - [License](#license)
<!-- start include in docs -->
> Deduce 2.0.0 has been released! It includes a 10x speedup, and way more features for customizing and tailoring. Some small changes are needed to keep going from version 1, read more about it here: [docs/migrating-to-v2](https://deduce.readthedocs.io/en/latest/migrating.html)
De-identify clinial text written in Dutch using `deduce`, a rule-based de-identification method for Dutch clinical text.
The development, principles and validation of `deduce` were initially described in [Menger et al. (2017)](http://www.sciencedirect.com/science/article/pii/S0736585316307365). De-identification of clinical text is needed for using text data for analysis, to comply with legal requirements and to protect the privacy of patients. Our rule-based method removes Protected Health Information (PHI) in the following categories:
* Person names, including initials
* Geographical locations smaller than a country
* Names of institutions that are related to patient treatment
* Dates
* Ages
* Patient numbers
* Telephone numbers
* E-mail addresses and URLs
If you use `deduce`, please cite the following paper:
[Menger, V.J., Scheepers, F., van Wijk, L.M., Spruit, M. (2017). DEDUCE: A pattern matching method for automatic de-identification of Dutch medical text, Telematics and Informatics, 2017, ISSN 0736-5853](http://www.sciencedirect.com/science/article/pii/S0736585316307365)
## Installation
``` python
pip install deduce
```
## Versions
For most cases the latest version is suitable, but some specific milestones are:
* `2.0.0` - Major refactor, with speedups, many new options for customizing, functionally very similar to original
* `1.0.8` - Small bugfixes compared to original release
* `1.0.1` - Original release with [Menger et al. (2017)](http://www.sciencedirect.com/science/article/pii/S0736585316307365)
Detailed versioning information is accessible in the [changelog](CHANGELOG.md).
<!-- end include in docs -->
<!-- start getting started -->
## Getting started
The basic way to use `deduce`, is to pass text to the `deidentify` method of a `Deduce` object:
```python
from deduce import Deduce
deduce = Deduce()
text = """Dit is stukje tekst met daarin de naam Jan Jansen. De patient J. Jansen
(e: j.jnsen@email.com, t: 06-12345678) is 64 jaar oud en woonachtig
in Utrecht. Hij werd op 10 oktober door arts Peter de Visser ontslagen
van de kliniek van het UMCU."""
doc = deduce.deidentify(text)
```
The output is available in the `Document` object:
```python
from pprint import pprint
pprint(doc.annotations)
AnnotationSet({Annotation(text='Jan Jansen', start_char=39, end_char=49, tag='persoon', length=10),
Annotation(text='Peter de Visser', start_char=185, end_char=200, tag='persoon', length=15),
Annotation(text='j.jnsen@email.com', start_char=76, end_char=93, tag='url', length=17),
Annotation(text='10 oktober', start_char=164, end_char=174, tag='datum', length=10),
Annotation(text='patient J. Jansen', start_char=54, end_char=71, tag='persoon', length=17),
Annotation(text='64', start_char=114, end_char=116, tag='leeftijd', length=2),
Annotation(text='UMCU', start_char=234, end_char=238, tag='instelling', length=4),
Annotation(text='06-12345678', start_char=98, end_char=109, tag='telefoonnummer', length=11),
Annotation(text='Utrecht', start_char=143, end_char=150, tag='locatie', length=7)})
print(doc.deidentified_text)
"""Dit is stukje tekst met daarin de naam <PERSOON-1>. De <PERSOON-2>
(e: <URL-1>, t: <TELEFOONNUMMER-1>) is <LEEFTIJD-1> jaar oud en woonachtig
in <LOCATIE-1>. Hij werd op <DATUM-1> door arts <PERSOON-3> ontslagen
van de kliniek van het <INSTELLING-1>."""
```
Aditionally, if the names of the patient are known, they may be added as `metadata`, where they will be picked up by `deduce`:
```python
from deduce.person import Person
patient = Person(first_names=["Jan"], initials="JJ", surname="Jansen")
doc = deduce.deidentify(text, metadata={'patient': patient})
print (doc.deidentified_text)
"""Dit is stukje tekst met daarin de naam <PATIENT>. De <PATIENT>
(e: <URL-1>, t: <TELEFOONNUMMER-1>) is <LEEFTIJD-1> jaar oud en woonachtig
in <LOCATIE-1>. Hij werd op <DATUM-1> door arts <PERSOON-1> ontslagen
van de kliniek van het <INSTELLING-1>."""
```
As you can see, adding known names keeps references to `<PATIENT>` in text. It also increases recall, as not all known names are contained in the lookup lists.
<!-- end getting started -->
## Documentation
A more extensive tutorial on using, configuring and modifying `deduce` is available at: [docs/tutorial](https://deduce.readthedocs.io/en/latest/tutorial.html)
Basic documentation and API are available at: [docs](https://deduce.readthedocs.io/en/latest/)
## Contributing
For setting up the dev environment and contributing guidelines, see: [docs/contributing](https://deduce.readthedocs.io/en/latest/contributing.html)
## Authors
* **Vincent Menger** - *Initial work*
* **Jonathan de Bruin** - *Code review*
* **Pablo Mosteiro** - *Bug fixes, structured annotations*
## License
This project is licensed under the GNU LGPLv3 license - see the [LICENSE.md](LICENSE.md) file for details
%package -n python3-deduce
Summary: Deduce: de-identification method for Dutch medical text
Provides: python-deduce
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-deduce
# deduce
[](https://github.com/vmenger/deduce/actions/workflows/test.yml)
[](https://coveralls.io/github/vmenger/deduce?branch=master)
[](https://github.com/vmenger/deduce/actions/workflows/build.yml)
[](https://deduce.readthedocs.io/en/latest/?badge=latest)
[](https://github.com/psf/black)
[Installation](#installation) - [Versions](#versions) - [Getting Started](#getting-started) - [Documentation](#documentation) - [Contributiong](#contributing) - [Authors](#authors) - [License](#license)
<!-- start include in docs -->
> Deduce 2.0.0 has been released! It includes a 10x speedup, and way more features for customizing and tailoring. Some small changes are needed to keep going from version 1, read more about it here: [docs/migrating-to-v2](https://deduce.readthedocs.io/en/latest/migrating.html)
De-identify clinial text written in Dutch using `deduce`, a rule-based de-identification method for Dutch clinical text.
The development, principles and validation of `deduce` were initially described in [Menger et al. (2017)](http://www.sciencedirect.com/science/article/pii/S0736585316307365). De-identification of clinical text is needed for using text data for analysis, to comply with legal requirements and to protect the privacy of patients. Our rule-based method removes Protected Health Information (PHI) in the following categories:
* Person names, including initials
* Geographical locations smaller than a country
* Names of institutions that are related to patient treatment
* Dates
* Ages
* Patient numbers
* Telephone numbers
* E-mail addresses and URLs
If you use `deduce`, please cite the following paper:
[Menger, V.J., Scheepers, F., van Wijk, L.M., Spruit, M. (2017). DEDUCE: A pattern matching method for automatic de-identification of Dutch medical text, Telematics and Informatics, 2017, ISSN 0736-5853](http://www.sciencedirect.com/science/article/pii/S0736585316307365)
## Installation
``` python
pip install deduce
```
## Versions
For most cases the latest version is suitable, but some specific milestones are:
* `2.0.0` - Major refactor, with speedups, many new options for customizing, functionally very similar to original
* `1.0.8` - Small bugfixes compared to original release
* `1.0.1` - Original release with [Menger et al. (2017)](http://www.sciencedirect.com/science/article/pii/S0736585316307365)
Detailed versioning information is accessible in the [changelog](CHANGELOG.md).
<!-- end include in docs -->
<!-- start getting started -->
## Getting started
The basic way to use `deduce`, is to pass text to the `deidentify` method of a `Deduce` object:
```python
from deduce import Deduce
deduce = Deduce()
text = """Dit is stukje tekst met daarin de naam Jan Jansen. De patient J. Jansen
(e: j.jnsen@email.com, t: 06-12345678) is 64 jaar oud en woonachtig
in Utrecht. Hij werd op 10 oktober door arts Peter de Visser ontslagen
van de kliniek van het UMCU."""
doc = deduce.deidentify(text)
```
The output is available in the `Document` object:
```python
from pprint import pprint
pprint(doc.annotations)
AnnotationSet({Annotation(text='Jan Jansen', start_char=39, end_char=49, tag='persoon', length=10),
Annotation(text='Peter de Visser', start_char=185, end_char=200, tag='persoon', length=15),
Annotation(text='j.jnsen@email.com', start_char=76, end_char=93, tag='url', length=17),
Annotation(text='10 oktober', start_char=164, end_char=174, tag='datum', length=10),
Annotation(text='patient J. Jansen', start_char=54, end_char=71, tag='persoon', length=17),
Annotation(text='64', start_char=114, end_char=116, tag='leeftijd', length=2),
Annotation(text='UMCU', start_char=234, end_char=238, tag='instelling', length=4),
Annotation(text='06-12345678', start_char=98, end_char=109, tag='telefoonnummer', length=11),
Annotation(text='Utrecht', start_char=143, end_char=150, tag='locatie', length=7)})
print(doc.deidentified_text)
"""Dit is stukje tekst met daarin de naam <PERSOON-1>. De <PERSOON-2>
(e: <URL-1>, t: <TELEFOONNUMMER-1>) is <LEEFTIJD-1> jaar oud en woonachtig
in <LOCATIE-1>. Hij werd op <DATUM-1> door arts <PERSOON-3> ontslagen
van de kliniek van het <INSTELLING-1>."""
```
Aditionally, if the names of the patient are known, they may be added as `metadata`, where they will be picked up by `deduce`:
```python
from deduce.person import Person
patient = Person(first_names=["Jan"], initials="JJ", surname="Jansen")
doc = deduce.deidentify(text, metadata={'patient': patient})
print (doc.deidentified_text)
"""Dit is stukje tekst met daarin de naam <PATIENT>. De <PATIENT>
(e: <URL-1>, t: <TELEFOONNUMMER-1>) is <LEEFTIJD-1> jaar oud en woonachtig
in <LOCATIE-1>. Hij werd op <DATUM-1> door arts <PERSOON-1> ontslagen
van de kliniek van het <INSTELLING-1>."""
```
As you can see, adding known names keeps references to `<PATIENT>` in text. It also increases recall, as not all known names are contained in the lookup lists.
<!-- end getting started -->
## Documentation
A more extensive tutorial on using, configuring and modifying `deduce` is available at: [docs/tutorial](https://deduce.readthedocs.io/en/latest/tutorial.html)
Basic documentation and API are available at: [docs](https://deduce.readthedocs.io/en/latest/)
## Contributing
For setting up the dev environment and contributing guidelines, see: [docs/contributing](https://deduce.readthedocs.io/en/latest/contributing.html)
## Authors
* **Vincent Menger** - *Initial work*
* **Jonathan de Bruin** - *Code review*
* **Pablo Mosteiro** - *Bug fixes, structured annotations*
## License
This project is licensed under the GNU LGPLv3 license - see the [LICENSE.md](LICENSE.md) file for details
%package help
Summary: Development documents and examples for deduce
Provides: python3-deduce-doc
%description help
# deduce
[](https://github.com/vmenger/deduce/actions/workflows/test.yml)
[](https://coveralls.io/github/vmenger/deduce?branch=master)
[](https://github.com/vmenger/deduce/actions/workflows/build.yml)
[](https://deduce.readthedocs.io/en/latest/?badge=latest)
[](https://github.com/psf/black)
[Installation](#installation) - [Versions](#versions) - [Getting Started](#getting-started) - [Documentation](#documentation) - [Contributiong](#contributing) - [Authors](#authors) - [License](#license)
<!-- start include in docs -->
> Deduce 2.0.0 has been released! It includes a 10x speedup, and way more features for customizing and tailoring. Some small changes are needed to keep going from version 1, read more about it here: [docs/migrating-to-v2](https://deduce.readthedocs.io/en/latest/migrating.html)
De-identify clinial text written in Dutch using `deduce`, a rule-based de-identification method for Dutch clinical text.
The development, principles and validation of `deduce` were initially described in [Menger et al. (2017)](http://www.sciencedirect.com/science/article/pii/S0736585316307365). De-identification of clinical text is needed for using text data for analysis, to comply with legal requirements and to protect the privacy of patients. Our rule-based method removes Protected Health Information (PHI) in the following categories:
* Person names, including initials
* Geographical locations smaller than a country
* Names of institutions that are related to patient treatment
* Dates
* Ages
* Patient numbers
* Telephone numbers
* E-mail addresses and URLs
If you use `deduce`, please cite the following paper:
[Menger, V.J., Scheepers, F., van Wijk, L.M., Spruit, M. (2017). DEDUCE: A pattern matching method for automatic de-identification of Dutch medical text, Telematics and Informatics, 2017, ISSN 0736-5853](http://www.sciencedirect.com/science/article/pii/S0736585316307365)
## Installation
``` python
pip install deduce
```
## Versions
For most cases the latest version is suitable, but some specific milestones are:
* `2.0.0` - Major refactor, with speedups, many new options for customizing, functionally very similar to original
* `1.0.8` - Small bugfixes compared to original release
* `1.0.1` - Original release with [Menger et al. (2017)](http://www.sciencedirect.com/science/article/pii/S0736585316307365)
Detailed versioning information is accessible in the [changelog](CHANGELOG.md).
<!-- end include in docs -->
<!-- start getting started -->
## Getting started
The basic way to use `deduce`, is to pass text to the `deidentify` method of a `Deduce` object:
```python
from deduce import Deduce
deduce = Deduce()
text = """Dit is stukje tekst met daarin de naam Jan Jansen. De patient J. Jansen
(e: j.jnsen@email.com, t: 06-12345678) is 64 jaar oud en woonachtig
in Utrecht. Hij werd op 10 oktober door arts Peter de Visser ontslagen
van de kliniek van het UMCU."""
doc = deduce.deidentify(text)
```
The output is available in the `Document` object:
```python
from pprint import pprint
pprint(doc.annotations)
AnnotationSet({Annotation(text='Jan Jansen', start_char=39, end_char=49, tag='persoon', length=10),
Annotation(text='Peter de Visser', start_char=185, end_char=200, tag='persoon', length=15),
Annotation(text='j.jnsen@email.com', start_char=76, end_char=93, tag='url', length=17),
Annotation(text='10 oktober', start_char=164, end_char=174, tag='datum', length=10),
Annotation(text='patient J. Jansen', start_char=54, end_char=71, tag='persoon', length=17),
Annotation(text='64', start_char=114, end_char=116, tag='leeftijd', length=2),
Annotation(text='UMCU', start_char=234, end_char=238, tag='instelling', length=4),
Annotation(text='06-12345678', start_char=98, end_char=109, tag='telefoonnummer', length=11),
Annotation(text='Utrecht', start_char=143, end_char=150, tag='locatie', length=7)})
print(doc.deidentified_text)
"""Dit is stukje tekst met daarin de naam <PERSOON-1>. De <PERSOON-2>
(e: <URL-1>, t: <TELEFOONNUMMER-1>) is <LEEFTIJD-1> jaar oud en woonachtig
in <LOCATIE-1>. Hij werd op <DATUM-1> door arts <PERSOON-3> ontslagen
van de kliniek van het <INSTELLING-1>."""
```
Aditionally, if the names of the patient are known, they may be added as `metadata`, where they will be picked up by `deduce`:
```python
from deduce.person import Person
patient = Person(first_names=["Jan"], initials="JJ", surname="Jansen")
doc = deduce.deidentify(text, metadata={'patient': patient})
print (doc.deidentified_text)
"""Dit is stukje tekst met daarin de naam <PATIENT>. De <PATIENT>
(e: <URL-1>, t: <TELEFOONNUMMER-1>) is <LEEFTIJD-1> jaar oud en woonachtig
in <LOCATIE-1>. Hij werd op <DATUM-1> door arts <PERSOON-1> ontslagen
van de kliniek van het <INSTELLING-1>."""
```
As you can see, adding known names keeps references to `<PATIENT>` in text. It also increases recall, as not all known names are contained in the lookup lists.
<!-- end getting started -->
## Documentation
A more extensive tutorial on using, configuring and modifying `deduce` is available at: [docs/tutorial](https://deduce.readthedocs.io/en/latest/tutorial.html)
Basic documentation and API are available at: [docs](https://deduce.readthedocs.io/en/latest/)
## Contributing
For setting up the dev environment and contributing guidelines, see: [docs/contributing](https://deduce.readthedocs.io/en/latest/contributing.html)
## Authors
* **Vincent Menger** - *Initial work*
* **Jonathan de Bruin** - *Code review*
* **Pablo Mosteiro** - *Bug fixes, structured annotations*
## License
This project is licensed under the GNU LGPLv3 license - see the [LICENSE.md](LICENSE.md) file for details
%prep
%autosetup -n deduce-2.0.3
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-deduce -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Wed May 31 2023 Python_Bot <Python_Bot@openeuler.org> - 2.0.3-1
- Package Spec generated
|
