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diff --git a/python-medcat.spec b/python-medcat.spec new file mode 100644 index 0000000..b25436e --- /dev/null +++ b/python-medcat.spec @@ -0,0 +1,326 @@ +%global _empty_manifest_terminate_build 0 +Name: python-medcat +Version: 1.7.0 +Release: 1 +Summary: Concept annotation tool for Electronic Health Records +License: MIT License +URL: https://github.com/CogStack/MedCAT +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/25/78/78d2e560a4ec76e52ada090cc0c5f9271f546de680246d0275ad7e31ee03/medcat-1.7.0.tar.gz +BuildArch: noarch + +Requires: python3-numpy +Requires: python3-pandas +Requires: python3-gensim +Requires: python3-spacy +Requires: python3-scipy +Requires: python3-transformers +Requires: python3-torch +Requires: python3-tqdm +Requires: python3-scikit-learn +Requires: python3-dill +Requires: python3-datasets +Requires: python3-jsonpickle +Requires: python3-psutil +Requires: python3-multiprocess +Requires: python3-py2neo +Requires: python3-aiofiles +Requires: python3-ipywidgets +Requires: python3-xxhash +Requires: python3-blis +Requires: python3-click +Requires: python3-pydantic +Requires: python3-aiohttp +Requires: python3-blis + +%description +# Medical <img src="https://github.com/CogStack/MedCAT/blob/master/media/cat-logo.png" width=45> oncept Annotation Tool + +[](https://github.com/CogStack/MedCAT/actions/workflows/main.yml?query=branch%3Amaster) +[](https://medcat.readthedocs.io/en/latest/?badge=latest) +[](https://github.com/CogStack/MedCAT/releases/latest) +[](https://pypi.org/project/medcat/) + +MedCAT can be used to extract information from Electronic Health Records (EHRs) and link it to biomedical ontologies like SNOMED-CT and UMLS. Paper on [arXiv](https://arxiv.org/abs/2010.01165). + +**Official Docs [here](https://medcat.readthedocs.io/en/latest/)** + +**Discussion Forum [discourse](https://discourse.cogstack.org/)** + +## Available Models + +We have 4 public models available: +1) UMLS Small (A modelpack containing a subset of UMLS (disorders, symptoms, medications...). Trained on MIMIC-III) +2) SNOMED International (Full SNOMED modelpack trained on MIMIC-III) +3) UMLS Dutch v1.10 (a modelpack provided by UMC Utrecht containing [UMLS entities with Dutch names](https://github.com/umcu/dutch-umls) trained on Dutch medical wikipedia articles and a negation detection model [repository](https://github.com/umcu/negation-detection/)/[paper](https://doi.org/10.48550/arxiv.2209.00470) trained on EMC Dutch Clinical Corpus). +4) UMLS Full. >4MM concepts trained self-supervsied on MIMIC-III. v2022AA of UMLS. + +To download any of these models, please [follow this link](https://uts.nlm.nih.gov/uts/login?service=https://medcat.rosalind.kcl.ac.uk/auth-callback) and sign into your NIH profile / UMLS license. You will then be redirected to the MedCAT model download form. Please complete this form and you will be provided a download link. + +## News +- **Paper** van Es, B., Reteig, L.C., Tan, S.C. et al. [Negation detection in Dutch clinical texts: an evaluation of rule-based and machine learning methods](https://doi.org/10.1186/s12859-022-05130-x). BMC Bioinformatics 24, 10 (2023). +- **New tool in the Cogstack ecosystem \[19. December 2022\]** [Foresight -- Deep Generative Modelling of Patient Timelines using Electronic Health Records](https://arxiv.org/abs/2212.08072) +- **New Paper using MedCAT \[21. October 2022\]**: [A New Public Corpus for Clinical Section Identification: MedSecId.](https://aclanthology.org/2022.coling-1.326.pdf) +- **Major Change to the Permissions of Use \[4. August 2022\]** MedCAT now uses the [Elastic License 2.0](https://github.com/CogStack/MedCAT/pull/271/commits/c9f4e86116ec751a97c618c97dadaa23e1feb6bc). For further information please click [here.](https://www.elastic.co/licensing/elastic-license) +- **New Downloader \[15. March 2022\]**: You can now [download](https://uts.nlm.nih.gov/uts/login?service=https://medcat.rosalind.kcl.ac.uk/auth-callback) the latest SNOMED-CT and UMLS model packs via UMLS user authentication. +- **New Feature and Tutorial \[7. December 2021\]**: [Exploring Electronic Health Records with MedCAT and Neo4j](https://towardsdatascience.com/exploring-electronic-health-records-with-medcat-and-neo4j-f376c03d8eef) +- **New Minor Release \[20. October 2021\]** Introducing model packs, new faster multiprocessing for large datasets (100M+ documents) and improved MetaCAT. +- **New Release \[1. August 2021\]**: Upgraded MedCAT to use spaCy v3, new scispaCy models have to be downloaded - all old CDBs (compatble with MedCAT v1) will work without any changes. +- **New Feature and Tutorial \[8. July 2021\]**: [Integrating 🤗 Transformers with MedCAT for biomedical NER+L](https://towardsdatascience.com/integrating-transformers-with-medcat-for-biomedical-ner-l-8869c76762a) +- **General \[1. April 2021\]**: MedCAT is upgraded to v1, unforunately this introduces breaking changes with older models (MedCAT v0.4), + as well as potential problems with all code that used the MedCAT package. MedCAT v0.4 is available on the legacy + branch and will still be supported until 1. July 2021 + (with respect to potential bug fixes), after it will still be available but not updated anymore. +- **Paper**: [What’s in a Summary? Laying the Groundwork for Advances in Hospital-Course Summarization](https://www.aclweb.org/anthology/2021.naacl-main.382.pdf) +- ([more...](https://github.com/CogStack/MedCAT/blob/master/media/news.md)) + +## Demo +A demo application is available at [MedCAT](https://medcat.rosalind.kcl.ac.uk). This was trained on MIMIC-III and all of SNOMED-CT. + +## Tutorials +A guide on how to use MedCAT is available at [MedCAT Tutorials](https://github.com/CogStack/MedCATtutorials). Read more about MedCAT on [Towards Data Science](https://towardsdatascience.com/medcat-introduction-analyzing-electronic-health-records-e1c420afa13a). + +## Logging +Since MedCAT is primarily a library, logging has been effectively disabled by default. The idea is that the user of the library should have the choice of what, where, and how to log the information from a specific library they are using. + +The idea is that the user can directly modify the logging behaviour of either the entire library or a certain set of modules within as they wish. We have provided a convenience method to add default handlers that log into the console as well as _medcat.log_ (`medcat.add_default_log_handlers`). + +Some details as to how one can configure the logging are described in the [MedCAT Tutorials](https://github.com/CogStack/MedCATtutorials). +PS: Currently (temporarily!) the tutorial is in the `tutorials` folder. + +## Acknowledgements +Entity extraction was trained on [MedMentions](https://github.com/chanzuckerberg/MedMentions) In total it has ~ 35K entites from UMLS + +The vocabulary was compiled from [Wiktionary](https://en.wiktionary.org/wiki/Wiktionary:Main_Page) In total ~ 800K unique words + +## Powered By +A big thank you goes to [spaCy](https://spacy.io/) and [Hugging Face](https://huggingface.co/) - who made life a million times easier. + + +## Citation +``` +@ARTICLE{Kraljevic2021-ln, + title="Multi-domain clinical natural language processing with {MedCAT}: The Medical Concept Annotation Toolkit", + author="Kraljevic, Zeljko and Searle, Thomas and Shek, Anthony and Roguski, Lukasz and Noor, Kawsar and Bean, Daniel and Mascio, Aurelie and Zhu, Leilei and Folarin, Amos A and Roberts, Angus and Bendayan, Rebecca and Richardson, Mark P and Stewart, Robert and Shah, Anoop D and Wong, Wai Keong and Ibrahim, Zina and Teo, James T and Dobson, Richard J B", + journal="Artif. Intell. Med.", + volume=117, + pages="102083", + month=jul, + year=2021, + issn="0933-3657", + doi="10.1016/j.artmed.2021.102083" +} +``` + + +%package -n python3-medcat +Summary: Concept annotation tool for Electronic Health Records +Provides: python-medcat +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-medcat +# Medical <img src="https://github.com/CogStack/MedCAT/blob/master/media/cat-logo.png" width=45> oncept Annotation Tool + +[](https://github.com/CogStack/MedCAT/actions/workflows/main.yml?query=branch%3Amaster) +[](https://medcat.readthedocs.io/en/latest/?badge=latest) +[](https://github.com/CogStack/MedCAT/releases/latest) +[](https://pypi.org/project/medcat/) + +MedCAT can be used to extract information from Electronic Health Records (EHRs) and link it to biomedical ontologies like SNOMED-CT and UMLS. Paper on [arXiv](https://arxiv.org/abs/2010.01165). + +**Official Docs [here](https://medcat.readthedocs.io/en/latest/)** + +**Discussion Forum [discourse](https://discourse.cogstack.org/)** + +## Available Models + +We have 4 public models available: +1) UMLS Small (A modelpack containing a subset of UMLS (disorders, symptoms, medications...). Trained on MIMIC-III) +2) SNOMED International (Full SNOMED modelpack trained on MIMIC-III) +3) UMLS Dutch v1.10 (a modelpack provided by UMC Utrecht containing [UMLS entities with Dutch names](https://github.com/umcu/dutch-umls) trained on Dutch medical wikipedia articles and a negation detection model [repository](https://github.com/umcu/negation-detection/)/[paper](https://doi.org/10.48550/arxiv.2209.00470) trained on EMC Dutch Clinical Corpus). +4) UMLS Full. >4MM concepts trained self-supervsied on MIMIC-III. v2022AA of UMLS. + +To download any of these models, please [follow this link](https://uts.nlm.nih.gov/uts/login?service=https://medcat.rosalind.kcl.ac.uk/auth-callback) and sign into your NIH profile / UMLS license. You will then be redirected to the MedCAT model download form. Please complete this form and you will be provided a download link. + +## News +- **Paper** van Es, B., Reteig, L.C., Tan, S.C. et al. [Negation detection in Dutch clinical texts: an evaluation of rule-based and machine learning methods](https://doi.org/10.1186/s12859-022-05130-x). BMC Bioinformatics 24, 10 (2023). +- **New tool in the Cogstack ecosystem \[19. December 2022\]** [Foresight -- Deep Generative Modelling of Patient Timelines using Electronic Health Records](https://arxiv.org/abs/2212.08072) +- **New Paper using MedCAT \[21. October 2022\]**: [A New Public Corpus for Clinical Section Identification: MedSecId.](https://aclanthology.org/2022.coling-1.326.pdf) +- **Major Change to the Permissions of Use \[4. August 2022\]** MedCAT now uses the [Elastic License 2.0](https://github.com/CogStack/MedCAT/pull/271/commits/c9f4e86116ec751a97c618c97dadaa23e1feb6bc). For further information please click [here.](https://www.elastic.co/licensing/elastic-license) +- **New Downloader \[15. March 2022\]**: You can now [download](https://uts.nlm.nih.gov/uts/login?service=https://medcat.rosalind.kcl.ac.uk/auth-callback) the latest SNOMED-CT and UMLS model packs via UMLS user authentication. +- **New Feature and Tutorial \[7. December 2021\]**: [Exploring Electronic Health Records with MedCAT and Neo4j](https://towardsdatascience.com/exploring-electronic-health-records-with-medcat-and-neo4j-f376c03d8eef) +- **New Minor Release \[20. October 2021\]** Introducing model packs, new faster multiprocessing for large datasets (100M+ documents) and improved MetaCAT. +- **New Release \[1. August 2021\]**: Upgraded MedCAT to use spaCy v3, new scispaCy models have to be downloaded - all old CDBs (compatble with MedCAT v1) will work without any changes. +- **New Feature and Tutorial \[8. July 2021\]**: [Integrating 🤗 Transformers with MedCAT for biomedical NER+L](https://towardsdatascience.com/integrating-transformers-with-medcat-for-biomedical-ner-l-8869c76762a) +- **General \[1. April 2021\]**: MedCAT is upgraded to v1, unforunately this introduces breaking changes with older models (MedCAT v0.4), + as well as potential problems with all code that used the MedCAT package. MedCAT v0.4 is available on the legacy + branch and will still be supported until 1. July 2021 + (with respect to potential bug fixes), after it will still be available but not updated anymore. +- **Paper**: [What’s in a Summary? Laying the Groundwork for Advances in Hospital-Course Summarization](https://www.aclweb.org/anthology/2021.naacl-main.382.pdf) +- ([more...](https://github.com/CogStack/MedCAT/blob/master/media/news.md)) + +## Demo +A demo application is available at [MedCAT](https://medcat.rosalind.kcl.ac.uk). This was trained on MIMIC-III and all of SNOMED-CT. + +## Tutorials +A guide on how to use MedCAT is available at [MedCAT Tutorials](https://github.com/CogStack/MedCATtutorials). Read more about MedCAT on [Towards Data Science](https://towardsdatascience.com/medcat-introduction-analyzing-electronic-health-records-e1c420afa13a). + +## Logging +Since MedCAT is primarily a library, logging has been effectively disabled by default. The idea is that the user of the library should have the choice of what, where, and how to log the information from a specific library they are using. + +The idea is that the user can directly modify the logging behaviour of either the entire library or a certain set of modules within as they wish. We have provided a convenience method to add default handlers that log into the console as well as _medcat.log_ (`medcat.add_default_log_handlers`). + +Some details as to how one can configure the logging are described in the [MedCAT Tutorials](https://github.com/CogStack/MedCATtutorials). +PS: Currently (temporarily!) the tutorial is in the `tutorials` folder. + +## Acknowledgements +Entity extraction was trained on [MedMentions](https://github.com/chanzuckerberg/MedMentions) In total it has ~ 35K entites from UMLS + +The vocabulary was compiled from [Wiktionary](https://en.wiktionary.org/wiki/Wiktionary:Main_Page) In total ~ 800K unique words + +## Powered By +A big thank you goes to [spaCy](https://spacy.io/) and [Hugging Face](https://huggingface.co/) - who made life a million times easier. + + +## Citation +``` +@ARTICLE{Kraljevic2021-ln, + title="Multi-domain clinical natural language processing with {MedCAT}: The Medical Concept Annotation Toolkit", + author="Kraljevic, Zeljko and Searle, Thomas and Shek, Anthony and Roguski, Lukasz and Noor, Kawsar and Bean, Daniel and Mascio, Aurelie and Zhu, Leilei and Folarin, Amos A and Roberts, Angus and Bendayan, Rebecca and Richardson, Mark P and Stewart, Robert and Shah, Anoop D and Wong, Wai Keong and Ibrahim, Zina and Teo, James T and Dobson, Richard J B", + journal="Artif. Intell. Med.", + volume=117, + pages="102083", + month=jul, + year=2021, + issn="0933-3657", + doi="10.1016/j.artmed.2021.102083" +} +``` + + +%package help +Summary: Development documents and examples for medcat +Provides: python3-medcat-doc +%description help +# Medical <img src="https://github.com/CogStack/MedCAT/blob/master/media/cat-logo.png" width=45> oncept Annotation Tool + +[](https://github.com/CogStack/MedCAT/actions/workflows/main.yml?query=branch%3Amaster) +[](https://medcat.readthedocs.io/en/latest/?badge=latest) +[](https://github.com/CogStack/MedCAT/releases/latest) +[](https://pypi.org/project/medcat/) + +MedCAT can be used to extract information from Electronic Health Records (EHRs) and link it to biomedical ontologies like SNOMED-CT and UMLS. Paper on [arXiv](https://arxiv.org/abs/2010.01165). + +**Official Docs [here](https://medcat.readthedocs.io/en/latest/)** + +**Discussion Forum [discourse](https://discourse.cogstack.org/)** + +## Available Models + +We have 4 public models available: +1) UMLS Small (A modelpack containing a subset of UMLS (disorders, symptoms, medications...). Trained on MIMIC-III) +2) SNOMED International (Full SNOMED modelpack trained on MIMIC-III) +3) UMLS Dutch v1.10 (a modelpack provided by UMC Utrecht containing [UMLS entities with Dutch names](https://github.com/umcu/dutch-umls) trained on Dutch medical wikipedia articles and a negation detection model [repository](https://github.com/umcu/negation-detection/)/[paper](https://doi.org/10.48550/arxiv.2209.00470) trained on EMC Dutch Clinical Corpus). +4) UMLS Full. >4MM concepts trained self-supervsied on MIMIC-III. v2022AA of UMLS. + +To download any of these models, please [follow this link](https://uts.nlm.nih.gov/uts/login?service=https://medcat.rosalind.kcl.ac.uk/auth-callback) and sign into your NIH profile / UMLS license. You will then be redirected to the MedCAT model download form. Please complete this form and you will be provided a download link. + +## News +- **Paper** van Es, B., Reteig, L.C., Tan, S.C. et al. [Negation detection in Dutch clinical texts: an evaluation of rule-based and machine learning methods](https://doi.org/10.1186/s12859-022-05130-x). BMC Bioinformatics 24, 10 (2023). +- **New tool in the Cogstack ecosystem \[19. December 2022\]** [Foresight -- Deep Generative Modelling of Patient Timelines using Electronic Health Records](https://arxiv.org/abs/2212.08072) +- **New Paper using MedCAT \[21. October 2022\]**: [A New Public Corpus for Clinical Section Identification: MedSecId.](https://aclanthology.org/2022.coling-1.326.pdf) +- **Major Change to the Permissions of Use \[4. August 2022\]** MedCAT now uses the [Elastic License 2.0](https://github.com/CogStack/MedCAT/pull/271/commits/c9f4e86116ec751a97c618c97dadaa23e1feb6bc). For further information please click [here.](https://www.elastic.co/licensing/elastic-license) +- **New Downloader \[15. March 2022\]**: You can now [download](https://uts.nlm.nih.gov/uts/login?service=https://medcat.rosalind.kcl.ac.uk/auth-callback) the latest SNOMED-CT and UMLS model packs via UMLS user authentication. +- **New Feature and Tutorial \[7. December 2021\]**: [Exploring Electronic Health Records with MedCAT and Neo4j](https://towardsdatascience.com/exploring-electronic-health-records-with-medcat-and-neo4j-f376c03d8eef) +- **New Minor Release \[20. October 2021\]** Introducing model packs, new faster multiprocessing for large datasets (100M+ documents) and improved MetaCAT. +- **New Release \[1. August 2021\]**: Upgraded MedCAT to use spaCy v3, new scispaCy models have to be downloaded - all old CDBs (compatble with MedCAT v1) will work without any changes. +- **New Feature and Tutorial \[8. July 2021\]**: [Integrating 🤗 Transformers with MedCAT for biomedical NER+L](https://towardsdatascience.com/integrating-transformers-with-medcat-for-biomedical-ner-l-8869c76762a) +- **General \[1. April 2021\]**: MedCAT is upgraded to v1, unforunately this introduces breaking changes with older models (MedCAT v0.4), + as well as potential problems with all code that used the MedCAT package. MedCAT v0.4 is available on the legacy + branch and will still be supported until 1. July 2021 + (with respect to potential bug fixes), after it will still be available but not updated anymore. +- **Paper**: [What’s in a Summary? Laying the Groundwork for Advances in Hospital-Course Summarization](https://www.aclweb.org/anthology/2021.naacl-main.382.pdf) +- ([more...](https://github.com/CogStack/MedCAT/blob/master/media/news.md)) + +## Demo +A demo application is available at [MedCAT](https://medcat.rosalind.kcl.ac.uk). This was trained on MIMIC-III and all of SNOMED-CT. + +## Tutorials +A guide on how to use MedCAT is available at [MedCAT Tutorials](https://github.com/CogStack/MedCATtutorials). Read more about MedCAT on [Towards Data Science](https://towardsdatascience.com/medcat-introduction-analyzing-electronic-health-records-e1c420afa13a). + +## Logging +Since MedCAT is primarily a library, logging has been effectively disabled by default. The idea is that the user of the library should have the choice of what, where, and how to log the information from a specific library they are using. + +The idea is that the user can directly modify the logging behaviour of either the entire library or a certain set of modules within as they wish. We have provided a convenience method to add default handlers that log into the console as well as _medcat.log_ (`medcat.add_default_log_handlers`). + +Some details as to how one can configure the logging are described in the [MedCAT Tutorials](https://github.com/CogStack/MedCATtutorials). +PS: Currently (temporarily!) the tutorial is in the `tutorials` folder. + +## Acknowledgements +Entity extraction was trained on [MedMentions](https://github.com/chanzuckerberg/MedMentions) In total it has ~ 35K entites from UMLS + +The vocabulary was compiled from [Wiktionary](https://en.wiktionary.org/wiki/Wiktionary:Main_Page) In total ~ 800K unique words + +## Powered By +A big thank you goes to [spaCy](https://spacy.io/) and [Hugging Face](https://huggingface.co/) - who made life a million times easier. + + +## Citation +``` +@ARTICLE{Kraljevic2021-ln, + title="Multi-domain clinical natural language processing with {MedCAT}: The Medical Concept Annotation Toolkit", + author="Kraljevic, Zeljko and Searle, Thomas and Shek, Anthony and Roguski, Lukasz and Noor, Kawsar and Bean, Daniel and Mascio, Aurelie and Zhu, Leilei and Folarin, Amos A and Roberts, Angus and Bendayan, Rebecca and Richardson, Mark P and Stewart, Robert and Shah, Anoop D and Wong, Wai Keong and Ibrahim, Zina and Teo, James T and Dobson, Richard J B", + journal="Artif. Intell. Med.", + volume=117, + pages="102083", + month=jul, + year=2021, + issn="0933-3657", + doi="10.1016/j.artmed.2021.102083" +} +``` + + +%prep +%autosetup -n medcat-1.7.0 + +%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-medcat -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 1.7.0-1 +- Package Spec generated |