Commit new tools

_data/tools.json

@@ -48,7 +48,7 @@
       "modified": "2023-05-14 20:23:06.333000",
       "description": "This application runs in the background and identifies other people running the app within the local area by using low energy Bluetooth. While the app is running permanently in the background, it periodically broadcasts and listens for other Bluetooth-enabled devices (iOS and Android at this time) that also broadcast the same unique identifier.",
       "license": "MIT",
-      "views": 229,
+      "views": 230,
       "category": "Mobile Application",
       "relations": [],
       "keywords": [
@@ -2029,7 +2029,7 @@
       "modified": "2023-03-31 16:02:45.278000",
       "description": "A medical concept annotation system that can be used to extract, structure and organize Health Records. It is based on unsupervised learning with the option of online/supervised learning via the MedCATtrainer interface. \n\n### Results & Insights\n\nThe initial motivation was temporal modelling of patients and diseases given the information in free text. But later we added nearly anything that in some way requires the information in free text to be structured.  ",
       "license": "Apache License 2.0",
-      "views": 43,
+      "views": 44,
       "category": "NLP system",
       "relations": [],
       "keywords": [
@@ -2067,7 +2067,7 @@
       "modified": "2023-05-29 16:47:23.297000",
       "description": "We have trained and validated a dedicated NER system to identify 7 categories: dosage, drug, duration, form, frequency, route and strength. We used transfer learning and self-supervised pre-training on 2.1 million documents from MIMIC EHR. Strict and lenient micro F1 achieved = 0.89 (0.95). \n\n### Results & Insights\n\nThe model is trained in order to support the clinical NLP community with a robust and accurate NER model for further downstream tasks. The development was motivated by two main goals: accuracy and interoperability. The model is written in Python 3.6+ and is compatible with spaCy pipelines, which is a free software for general NLP tasks.",
       "license": "MIT",
-      "views": 30,
+      "views": 31,
       "category": "Named entity recognition (NER) model",
       "relations": [],
       "keywords": [
@@ -5404,7 +5404,7 @@
       "modified": "2023-01-02 09:11:08.334000",
       "description": "Application to extract MRI investigations.  Output Values: MRI Performed (Yes/No), MRI Result (Normal, Abnormal, Unknown)\n\n### Results & Insights\n\nResults of version 1 are available here - https://bmjopen.bmj.com/content/9/4/e023232",
       "license": "",
-      "views": 22,
+      "views": 23,
       "category": "NLP System",
       "relations": [],
       "keywords": [
@@ -5439,7 +5439,7 @@
       "modified": "2023-04-19 06:14:38.594000",
       "description": "Application to extract CT Scan investigations.  Output Values: CT Performed (Yes/No), CT Result (Normal, Abnormal, Unknown)\n\n### Results & Insights\n\nResults of version 1 are available here - https://bmjopen.bmj.com/content/9/4/e023232",
       "license": "",
-      "views": 24,
+      "views": 25,
       "category": "NLP System",
       "relations": [],
       "keywords": [
@@ -6391,7 +6391,7 @@
       "modified": "2023-09-21 17:54:36.915000",
       "description": "The Catalogue of Mental Health Measures is designed to provide easy access to information about the mental health measures included in UK cohort and longitudinal studies to maximise the uptake of existing data and facilitate mental health research.\n\nThe Catalogue provides descriptions of the studies as well as the instruments used to assess mental health and wellbeing. It also includes details on each measure such as the items, informants, response scale and reporting period. Users can explore existing data by searching for a specific study, a mental health topic, or an instrument. \n\nBy providing details of the measures and studies, the Catalogue serves as a resource for researchers to identify datasets that include mental health and wellbeing measures, plan harmonisation studies, and plan further data collection.\n\n\n### Results & Insights\n\nThe Catalogue of Mental Health Measures features over 55 cohort studies, more than 4,000 measures of mental health and wellbeing, and covers 30+ mental health topics. \n\nThe Catalogue includes a range of study types, including birth cohorts, twin studies, repeated cross-sectional studies, accelerated longitudinal and household panel designs. Some were specifically designed to focus on mental health, while others have included mental health measures within a more multi-purpose context.\n",
       "license": "",
-      "views": 202,
+      "views": 203,
       "category": "Dataset discovery tool",
       "relations": [],
       "keywords": [
@@ -6480,7 +6480,7 @@
       "modified": "2023-05-30 11:44:01.318000",
       "description": "Part of a set of infographics developed by Health Data Research UK that help explain some of the Gateway's key functionalities in an easy to understand format as well as some of the other programmes and services available at HRD UK. \n\nThis one relates to the Cohort Discovery Tool - where Gateway users can search and request access to all potential datasets across a population that precisely match the requirements of a research project. \n\nFree for all to download, use and share but please credit the Health Data Research Innovation Gateway when using this tool. ",
       "license": "CC BY NC 3.0",
-      "views": 105,
+      "views": 106,
       "category": "infographic",
       "relations": [],
       "keywords": [
@@ -6955,7 +6955,7 @@
       "modified": "2023-07-03 07:19:22.398000",
       "description": "CamCOPS is an open-source application for capturing information relevant for cognitive and psychiatric assessment, on tablets, laptops, and desktops. It offers simple questionnaires and more complex tasks, and sends its data securely to your server.\n\n### Results & Insights\n\nReference paper: Cardinal RN, Burchell M (2021). The Cambridge Cognitive and Psychiatric Assessment Kit (CamCOPS): a secure open-source client-server system for mobile research and clinical data capture. Frontiers in Psychiatry 12: 578298. https://pubmed.ncbi.nlm.nih.gov/34867492/; https://doi.org/10.3389/fpsyt.2021.578298.\n\nSource code is at https://github.com/ucam-department-of-psychiatry/crate",
       "license": "GNU General Public License version 3.0 (GPLv3)",
-      "views": 35,
+      "views": 37,
       "category": "Mobile Application",
       "relations": [],
       "keywords": [

_data/tools.yaml

@@ -49,7 +49,7 @@ tools:
   relations: []
   type: ''
   uploader: ''
-  views: 229
+  views: 230
 - '@schema':
     type: tool
   _id: 19003
@@ -2198,7 +2198,7 @@ tools:
   relations: []
   type: ''
   uploader: 20203192139498904
-  views: 43
+  views: 44
 - '@schema':
     type: tool
   _id: 34437455080619684
@@ -2238,7 +2238,7 @@ tools:
   relations: []
   type: ''
   uploader: 20203192139498904
-  views: 30
+  views: 31
 - '@schema':
     type: tool
   _id: 5330147649379575
@@ -5915,7 +5915,7 @@ tools:
   relations: []
   type: ''
   uploader: 2742415330560255
-  views: 22
+  views: 23
 - '@schema':
     type: tool
   _id: 8356186742156964
@@ -5949,7 +5949,7 @@ tools:
   relations: []
   type: ''
   uploader: 2742415330560255
-  views: 24
+  views: 25
 - '@schema':
     type: tool
   _id: 47757674439076728
@@ -6931,7 +6931,7 @@ tools:
   relations: []
   type: ''
   uploader: 6045838202930374
-  views: 202
+  views: 203
 - '@schema':
     type: tool
   _id: 6231490526322994
@@ -7035,7 +7035,7 @@ tools:
   relations: []
   type: ''
   uploader: 6545332055051722
-  views: 105
+  views: 106
 - '@schema':
     type: tool
   _id: 9856286733786312
@@ -7514,7 +7514,7 @@ tools:
   relations: []
   type: ''
   uploader: 5648313829043343
-  views: 35
+  views: 37
 - '@schema':
     type: tool
   _id: 5372816439598571