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Susheel Varma
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| "modified": "2023-05-06 11:22:38.114000", | ||
| "description": "Utility SQL platform for data definition, extraction, manipulation and persistance.", | ||
| "license": "MS", | ||
| "views": 122, | ||
| "views": 123, | ||
| "category": "Data Modelling, Data Visualisation, Developer stack", | ||
| "relations": [], | ||
| "keywords": [ | ||
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| "modified": "2023-05-12 06:51:39.083000", | ||
| "description": "Datamartist is a low cost flexible, visual, data profiling and data transformation tool. It can read data from data sources (such as files, or relational databases), do data transformations using a simple, visual user interface, and then can write the results into files or databases. By combining a flexible ETL tool with data profiling capabilities, Datamartist is a fast and easy way to both do ad-hoc data profiling, and to set up automated data quality monitoring.\nFor a wide range of data transformation requirements, Datamartist is the only tool required, giving a fast and flexible ETL capability to pull all sorts of data from all sorts of sources.\n\n-Profile your data\n-Find Data Quality Issues\n-Excel Import and Export", | ||
| "license": "Proprietary", | ||
| "views": 59, | ||
| "views": 60, | ||
| "category": "Data Profiling/Transformation Tool", | ||
| "relations": [], | ||
| "keywords": [ | ||
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@@ -1961,7 +1961,7 @@ | |
| "modified": "2023-03-26 09:52:45.293000", | ||
| "description": "Medication dosage instructions in electronic health records are often in the form of text rather than numbers. This program is designed to convert the text into numbers for the dose, frequency, units, duration etc.\n\n### Results & Insights\n\nThis is a rule-based algorithm for converting text dosage instructions into a structured form, designed for pharmacoepidemiology studies in primary care databases. When run in batch mode, the algorithm identifies unique dosage strings and uses a series of regular expressions to standardise the wording, then applies numerical extraction algorithms to extract dose number, frequency etc. and calculate the daily dose. It also flags if the instructions specify a dose range or state a maximum dose, or if it is an 'as required' prescription.\n\nThe algorithm can be run as an R service and called from other applications such as Python. \n\nThe original version of the algorithm was in Visual Basic, and it has been ported to R.", | ||
| "license": "GNU General Public License version 3.0 (GPLv3)", | ||
| "views": 49, | ||
| "views": 51, | ||
| "category": "Rule-based NLP system for converting text dosage instructions into a structured form", | ||
| "relations": [], | ||
| "keywords": [ | ||
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@@ -3010,7 +3010,7 @@ | |
| "modified": "2023-05-01 00:51:49.035000", | ||
| "description": "Application to identify instances of hopelessness.\n\nBoth past and present symptom.\n\nOutput values: Positive, Negative and Unknown.\n\n### Results & Insights\n\nFor further details please visit the CRIS link provided", | ||
| "license": "Available upon request", | ||
| "views": 30, | ||
| "views": 31, | ||
| "category": "NLP System", | ||
| "relations": [], | ||
| "keywords": [ | ||
|
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@@ -4378,7 +4378,7 @@ | |
| "modified": "2022-12-24 20:49:06.622000", | ||
| "description": "To identify instances of cannabis use.\n\nBoth past and present symptom.\n\nOutput values: Positive, Negative and Unknown.\n\n### Results & Insights\n\nFor further details please visit the CRIS link provided", | ||
| "license": "Available upon request", | ||
| "views": 19, | ||
| "views": 20, | ||
| "category": "NLP System", | ||
| "relations": [], | ||
| "keywords": [ | ||
|
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@@ -5026,7 +5026,7 @@ | |
| "modified": "2023-05-23 13:16:46.141000", | ||
| "description": "An opensource platform that provides researchers with easy access to deploy collaborative workspace environments in the AWS Cloud, through a simple to use web interface. Offers the ability to operate across teams, universities, and datasets while enabling Research IT stakeholders to manage, monitor, and control spending, apply security best practices and comply with corporate governance.\n\nService Workbench targets Research workloads with out of the box service support for:\n\n JupyterLabs via Amazon SageMaker with Python Kernels\n Jupyter Notebooks on Amazon EMR + Hail v0.2\n RStudio on EC2\n Windows VM on Amazon EC2\n Linux VM on EC2\n\nAdditional product configuration can easily be added to Service Workbench through Service Catalog and be linked to researcher, institutional, and includes support for [AWS Open Data](https://registry.opendata.aws) data sets configured by Research IT for their researchers use across the institution.\n\nPlatform provides one-click option to admins for easier creation (vending) of new AWS accounts specific to researchers' teams for easier governance.\n\nThe code in the GitHub repo is fully functional but is intended as a stand-a-lone evaluation deployment and some foundational AWS knowledge is assumed.\n\nPlease contact the health research team at AWS for further information and support: [[email protected]](mailto:[email protected]); [[email protected]](mailto:[email protected]); [[email protected]](mailto:[email protected])", | ||
| "license": "Apache License 2.0", | ||
| "views": 467, | ||
| "views": 468, | ||
| "category": "Data Science Platform", | ||
| "relations": [], | ||
| "keywords": [ | ||
|
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@@ -5091,7 +5091,7 @@ | |
| "modified": "2023-05-03 07:37:30.360000", | ||
| "description": "COMETA is an entity linking dataset of layman medical terminology collected by analysing four years of content in 68 health-themed subreddits.\n\n### Results & Insights\n\nResults from benchmark experiments using the dataset can be found in this paper - https://www.aclweb.org/anthology/2020.emnlp-main.253/", | ||
| "license": "For a copy of the corpus, please follow instructions in the link - https://siphs.org/corpus", | ||
| "views": 59, | ||
| "views": 60, | ||
| "category": "Corpus for NLP research", | ||
| "relations": [], | ||
| "keywords": [ | ||
|
|
@@ -5231,7 +5231,7 @@ | |
| "modified": "2023-05-28 09:42:28.253000", | ||
| "description": "Bi\u014ckean\u00f3s is an open biomedical database catalogue and discovery tool aimed primarily at ML/AI community.\n\nIt concentrates on open datasets in natural and health sciences from multiple sources. From cell biology, chemistry, protein and molecule structure and classification through pathways, side and adverse effects, omics, to anonymised medical information and clinical standards. It merges the results with our private curated collection, reconciles the records, and augments them with information extracted from the scientific literature. \n\nIt navigates the researchers through the available datasets, helps them identify those important for their work, and facilitate their acquisition.\n\n### Results & Insights\n\n- Over 5000 sources\n- Refreshed weekly\n- Recommendations of similar datasources\n- Heuristic-based ranking to discover the most useful data in a given \n- Licensing information\n- References to other gateways records containing the data\n", | ||
| "license": "", | ||
| "views": 437, | ||
| "views": 438, | ||
| "category": "Dataset discovery tool", | ||
| "relations": [], | ||
| "keywords": [ | ||
|
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@@ -6193,7 +6193,7 @@ | |
| "modified": "2023-05-31 11:33:14.542000", | ||
| "description": "This interactive visualizations report focus on exploring unemployment and job loss in the COVID-19 UK from a gender, ethnicity, and class perpective.\n\nThe code of this dashboard is available here: https://github.com/luistorresr/gender_covid_uk/tree/main/Outputs/Report_1_unemployment\n\nThis tool is part of the research project \"How is COVID-19 impacting women and men's working lives in the UK?\" which is part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant ref MC_PC_20029).\n\n### Results & Insights\n\nThis is a report written in R Markdown for interactive data visualizations. Reports are produced as a word document and as an html file that can be uploded to a web hosting. \n\nVisualization can be adapted to create dashboards and monitor seudo-longitudinal trends.", | ||
| "license": "MIT license", | ||
| "views": 352, | ||
| "views": 353, | ||
| "category": "Data Visualisation", | ||
| "relations": [], | ||
| "keywords": [ | ||
|
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@@ -6318,7 +6318,7 @@ | |
| "modified": "2023-05-19 10:47:41.492000", | ||
| "description": "This interactive visualizations report focus on exploring how self-employment has changed since the COVID-19 pandemic in the UK\n\nThe code of this dashboard is available here: https://github.com/luistorresr/gender_covid_uk/tree/main/Outputs/Report_3_selfemployment\n\nThis tool is part of the research project \"How is COVID-19 impacting women and men's working lives in the UK?\" which is part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant ref MC_PC_20029).\n\n### Results & Insights\n\nThis is a report written in R Markdown for interactive data visualizations. Reports are produced as a word document and as an html file that can be uploded to a web hosting.\n\nVisualization can be adapted to create dashboards and monitor seudo-longitudinal trends.", | ||
| "license": "MIT license", | ||
| "views": 121, | ||
| "views": 122, | ||
| "category": "Data Visualisation", | ||
| "relations": [], | ||
| "keywords": [ | ||
|
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@@ -6724,7 +6724,7 @@ | |
| "modified": "2023-05-22 13:22:22.913000", | ||
| "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 how the Gateway is providing a single data access request process built around the Five Safes Framework.\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": [ | ||
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@@ -6815,7 +6815,7 @@ | |
| "modified": "2024-07-15 15:00:28.066000", | ||
| "description": "Carrot-Mapper enables conversion of data to the OMOP Common Data Model, without data being egressed from its secure location, nor requiring access to the secure location. Carrot-Mapper automates as much of the process as possible, and also enables users to reuse each others' mappings. Carrot-Mapper pairs with Carrot-CDM to complete the OMOP conversion process.", | ||
| "license": "MIT", | ||
| "views": 289, | ||
| "views": 290, | ||
| "category": "Web application", | ||
| "relations": [], | ||
| "keywords": [], | ||
|
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@@ -6965,7 +6965,7 @@ | |
| "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": 105, | ||
| "views": 107, | ||
| "category": "Mobile Application", | ||
| "relations": [], | ||
| "keywords": [ | ||
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