{"id":26699658,"url":"https://github.com/pythonhealthdatascience/stroke_rap_python","last_synced_at":"2025-03-26T23:16:00.630Z","repository":{"id":284579331,"uuid":"955363563","full_name":"pythonhealthdatascience/stroke_rap_python","owner":"pythonhealthdatascience","description":"Applying the Python DES RAP Template to the Stroke Capacity Planning Model from Monks et al. 2016","archived":false,"fork":false,"pushed_at":"2025-03-26T16:06:59.000Z","size":63729,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-26T16:30:52.768Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/pythonhealthdatascience.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-03-26T14:21:57.000Z","updated_at":"2025-03-26T16:06:58.000Z","dependencies_parsed_at":"2025-03-26T16:41:37.732Z","dependency_job_id":null,"html_url":"https://github.com/pythonhealthdatascience/stroke_rap_python","commit_stats":null,"previous_names":["pythonhealthdatascience/stroke_rap_python"],"tags_count":0,"template":false,"template_full_name":"pythonhealthdatascience/rap_template_python_des","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pythonhealthdatascience%2Fstroke_rap_python","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pythonhealthdatascience%2Fstroke_rap_python/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pythonhealthdatascience%2Fstroke_rap_python/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pythonhealthdatascience%2Fstroke_rap_python/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pythonhealthdatascience","download_url":"https://codeload.github.com/pythonhealthdatascience/stroke_rap_python/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245749900,"owners_count":20666086,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-03-26T23:16:00.121Z","updated_at":"2025-03-26T23:16:00.623Z","avatar_url":"https://github.com/pythonhealthdatascience.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n\n# Stroke capacity planning model: python DES RAP\n\n[![python](https://img.shields.io/badge/-Python_Version-blue?logo=python\u0026logoColor=white)](https://www.python.org/)\n![licence](https://img.shields.io/badge/Licence-MIT-green.svg?labelColor=gray)\n[![ORCID: Heather](https://img.shields.io/badge/ORCID_Amy_Heather-0000--0002--6596--3479-brightgreen)](https://orcid.org/0000-0002-6596-3479)\n\n\u003c/div\u003e\n\nThis repository applies the [Python DES RAP Template](https://github.com/pythonhealthdatascience/rap_template_python_des) to a real-life example:\n\n\u003e Monks T, Worthington D, Allen M, Pitt M, Stein K, James MA. A modelling tool for capacity planning in acute and community stroke services. BMC Health Serv Res. 2016 Sep 29;16(1):530. doi: [10.1186/s12913-016-1789-4](https://doi.org/10.1186/s12913-016-1789-4). PMID: 27688152; PMCID: PMC5043535.\n\n\u003cbr\u003e\n\n## Installation\n\nTBC\n\n\u003c!-- TODO: Provide instructions for installing dependencies and setting up the environment. --\u003e\n\n\u003cbr\u003e\n\n## How to run\n\nTBC\n\n\u003c!-- Provide step-by-step instructions and examples.\n\nClearly indicate which files will create each figure in the paper. Hypothetical example:\n\n* To generate **Figures 1 and 2**, execute `notebooks/base_case.ipynb`\n* To generate **Table 1** and **Figures 3 to 5**, execute `notebooks/scenario_analysis.ipynb` --\u003e\n\n\u003cbr\u003e\n\n## Run time and machine specification\n\nTBC\n\n\u003c!-- State the run time, and give the specification of the machine used (which achieved that run time).\n\n**Example:** Intel Core i7-12700H with 32GB RAM running Ubuntu 24.04.1 Linux. \n\nTo find this information:\n\n* **Linux:** Run `neofetch` on the terminal and record your CPU, memory and operating system.\n* **Windows:** Open \"Task Manager\" (Ctrl + Shift + Esc), go to the \"Performance\" tab, then select \"CPU\" and \"Memory\" for relevant information.\n* **Mac:** Click the \"Apple Menu\", select \"About This Mac\", then window will display the details.--\u003e\n\n\u003cbr\u003e\n\n## Citation\n\nIf you use this template, please cite:\n\n\u003e Heather, A. (2025). Stroke capacity planning model: python DES RAP. GitHub. https://github.com/pythonhealthdatascience/stroke_rap_python.\n\nA `CITATION.cff` file is also provided.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpythonhealthdatascience%2Fstroke_rap_python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpythonhealthdatascience%2Fstroke_rap_python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpythonhealthdatascience%2Fstroke_rap_python/lists"}