From 238681abb64bcd0c0dc265b070943b847527d554 Mon Sep 17 00:00:00 2001 From: mart-r Date: Mon, 23 Jun 2025 09:57:40 +0100 Subject: [PATCH 1/5] CU-869998jcj: Update demo link to the working one --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 2da4c17c..e7d489bd 100644 --- a/README.md +++ b/README.md @@ -54,7 +54,7 @@ To install the latest version of MedCAT without torch GPU support run the follow pip install medcat --extra-index-url https://download.pytorch.org/whl/cpu/ ``` ## 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. +A demo application is available at [MedCAT](https://medcat.sites.er.kcl.ac.uk). This was trained on MIMIC-III and all of SNOMED-CT. PS: This link can take a long time to load the first time around. The machine spins up as needed and spins down when inactive. ## Tutorials From 269663c4412c92b564aa68701573cf821d5cee00 Mon Sep 17 00:00:00 2001 From: mart-r Date: Mon, 23 Jun 2025 09:58:46 +0100 Subject: [PATCH 2/5] CU-869998jcj: Update model download links working ones --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index e7d489bd..95870f46 100644 --- a/README.md +++ b/README.md @@ -23,14 +23,14 @@ We have 4 public models available: 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-supervised 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. +To download any of these models, please [follow this link](https://uts.nlm.nih.gov/uts/login?service=https://medcat.sites.er.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 Downloader \[15. March 2022\]**: You can now [download](https://uts.nlm.nih.gov/uts/login?service=https://medcat.sites.er.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. From d79ddd00f9d5cef920dac5eb07c33cfaf8b83afd Mon Sep 17 00:00:00 2001 From: mart-r Date: Mon, 23 Jun 2025 10:00:40 +0100 Subject: [PATCH 3/5] CU-869998jcj: Add API-key based model download links --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 95870f46..28e0e735 100644 --- a/README.md +++ b/README.md @@ -23,14 +23,14 @@ We have 4 public models available: 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-supervised 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.sites.er.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. +To download any of these models, please [follow this link](https://uts.nlm.nih.gov/uts/login?service=https://medcat.sites.er.kcl.ac.uk/auth-callback) (or [this link for API key based download](https://medcat.sites.er.kcl.ac.uk/auth-callback-api)) 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.sites.er.kcl.ac.uk/auth-callback) the latest SNOMED-CT and UMLS model packs via UMLS user authentication. +- **New Downloader \[15. March 2022\]**: You can now [download](https://uts.nlm.nih.gov/uts/login?service=https://medcat.sites.er.kcl.ac.uk/auth-callback) (or [API key based download](https://medcat.sites.er.kcl.ac.uk/auth-callback-api)) 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. From f729920d6f3a0777447b44c0e995af090feeafb8 Mon Sep 17 00:00:00 2001 From: mart-r Date: Mon, 23 Jun 2025 10:02:04 +0100 Subject: [PATCH 4/5] CU-869998jcj: Update demo and download links in docs --- docs/main.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/main.md b/docs/main.md index b8796487..5618cade 100644 --- a/docs/main.md +++ b/docs/main.md @@ -11,12 +11,12 @@ MedCAT can be used to extract information from Electronic Health Records (EHRs) **Discussion Forum [here](https://discourse.cogstack.org/)** -**Available Models (requires UMLS license) [here](https://uts.nlm.nih.gov/uts/login?service=https://medcat.rosalind.kcl.ac.uk/auth-callback)** +**Available Models (requires UMLS license) [here](https://uts.nlm.nih.gov/uts/login?service=https://medcat.sites.er.kcl.ac.uk/auth-callback)** ## News - **Paper** [A New Public Corpus for Clinical Section Identification: MedSecId](https://aclanthology.org/2022.coling-1.326.pdf) - **New Release** \[5. October 2022\]**: Logging changes, and various small updates. [Full changelog](https://github.com/CogStack/MedCAT/compare/v1.3.0...v1.4.0) -- **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 Downloader \[15. March 2022\]**: You can now [download](https://uts.nlm.nih.gov/uts/login?service=https://medcat.sites.er.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. @@ -27,7 +27,7 @@ MedCAT can be used to extract information from Electronic Health Records (EHRs) (with respect to potential bug fixes), after it will still be available but not updated anymore. ## 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. +A demo application is available at [MedCAT](https://medcat.sites.er.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). @@ -116,7 +116,7 @@ python medcat/utils/model_creator.py tests/model_creator/config_example.yml ## Models ### SNOMED-CT and UMLS -If you have access to UMLS or SNOMED-CT, you can download the pre-built CDB and Vocab for those databases by signing in and filling out [the online form](https://uts.nlm.nih.gov/uts/login?service=https://medcat.rosalind.kcl.ac.uk/auth-callback). This link first requires you to authenticate your ontology access via the NIH portal. +If you have access to UMLS or SNOMED-CT, you can download the pre-built CDB and Vocab for those databases by signing in and filling out [the online form](https://uts.nlm.nih.gov/uts/login?service=https://medcat.sites.er.kcl.ac.uk/auth-callback). This link first requires you to authenticate your ontology access via the NIH portal. ### MedMentions A basic trained model is made public. It contains ~ 35K concepts available in `MedMentions`. This was compiled from MedMentions and does not have any data from [NLM](https://www.nlm.nih.gov/research/umls/) as that data is not publicaly available. From 9190beabae28f940004bacd0e4196d417fd68393 Mon Sep 17 00:00:00 2001 From: mart-r Date: Mon, 23 Jun 2025 10:03:31 +0100 Subject: [PATCH 5/5] CU-869998jcj: Add API download links to docs --- docs/main.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/main.md b/docs/main.md index 5618cade..c4bd6dbd 100644 --- a/docs/main.md +++ b/docs/main.md @@ -11,12 +11,12 @@ MedCAT can be used to extract information from Electronic Health Records (EHRs) **Discussion Forum [here](https://discourse.cogstack.org/)** -**Available Models (requires UMLS license) [here](https://uts.nlm.nih.gov/uts/login?service=https://medcat.sites.er.kcl.ac.uk/auth-callback)** +**Available Models (requires UMLS license) [here](https://uts.nlm.nih.gov/uts/login?service=https://medcat.sites.er.kcl.ac.uk/auth-callback) (or [this link for API key based download](https://medcat.sites.er.kcl.ac.uk/auth-callback-api))** ## News - **Paper** [A New Public Corpus for Clinical Section Identification: MedSecId](https://aclanthology.org/2022.coling-1.326.pdf) - **New Release** \[5. October 2022\]**: Logging changes, and various small updates. [Full changelog](https://github.com/CogStack/MedCAT/compare/v1.3.0...v1.4.0) -- **New Downloader \[15. March 2022\]**: You can now [download](https://uts.nlm.nih.gov/uts/login?service=https://medcat.sites.er.kcl.ac.uk/auth-callback) the latest SNOMED-CT and UMLS model packs via UMLS user authentication. +- **New Downloader \[15. March 2022\]**: You can now [download](https://uts.nlm.nih.gov/uts/login?service=https://medcat.sites.er.kcl.ac.uk/auth-callback) (or [API key download](https://medcat.sites.er.kcl.ac.uk/auth-callback-api)) 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. @@ -116,7 +116,7 @@ python medcat/utils/model_creator.py tests/model_creator/config_example.yml ## Models ### SNOMED-CT and UMLS -If you have access to UMLS or SNOMED-CT, you can download the pre-built CDB and Vocab for those databases by signing in and filling out [the online form](https://uts.nlm.nih.gov/uts/login?service=https://medcat.sites.er.kcl.ac.uk/auth-callback). This link first requires you to authenticate your ontology access via the NIH portal. +If you have access to UMLS or SNOMED-CT, you can download the pre-built CDB and Vocab for those databases by signing in and filling out [the online form](https://uts.nlm.nih.gov/uts/login?service=https://medcat.sites.er.kcl.ac.uk/auth-callback) (or [this link for API key based download](https://medcat.sites.er.kcl.ac.uk/auth-callback-api)). This link first requires you to authenticate your ontology access via the NIH portal. ### MedMentions A basic trained model is made public. It contains ~ 35K concepts available in `MedMentions`. This was compiled from MedMentions and does not have any data from [NLM](https://www.nlm.nih.gov/research/umls/) as that data is not publicaly available.