{"id":13829464,"url":"https://github.com/AiAiHealthcare/ProjectAiAi","last_synced_at":"2025-07-09T09:33:18.969Z","repository":{"id":109049496,"uuid":"68553801","full_name":"AiAiHealthcare/ProjectAiAi","owner":"AiAiHealthcare","description":"AiAi.care project is teaching computers to \"see\" chest X-rays and interpret them how a human Radiologist would. We are using 700,000 Chest X-Rays + Deep Learning to build an FDA 💊 approved, open-source screening tool for Tuberculosis and Lung Cancer. After an MRMC clinical trial, AiAi CAD will be distributed for free to emerging nations, charitable hospitals, and organizations like WHO 🌏 We will also release our pretrained models and weights as Medical Imagenet.","archived":false,"fork":false,"pushed_at":"2020-09-20T17:12:18.000Z","size":61,"stargazers_count":105,"open_issues_count":11,"forks_count":22,"subscribers_count":29,"default_branch":"master","last_synced_at":"2024-08-04T10:01:26.976Z","etag":null,"topics":["charity","convolutional-neural-networks","ct-scans","cxr-lungs","deep-learning","dicom","fda","keras","lung-cancer","lung-cancer-detection","postero-anterior","pytorch","radiologist","radiology","scikit-image","teleradiology","tensorflow","tuberculosis","x-ray"],"latest_commit_sha":null,"homepage":"https://AiAi.care/","language":"Dockerfile","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/AiAiHealthcare.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2016-09-18T23:51:46.000Z","updated_at":"2024-07-17T06:17:01.000Z","dependencies_parsed_at":null,"dependency_job_id":"2b88e051-4bc4-4194-8f65-f1942d8aa0f1","html_url":"https://github.com/AiAiHealthcare/ProjectAiAi","commit_stats":null,"previous_names":[],"tags_count":2,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AiAiHealthcare%2FProjectAiAi","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AiAiHealthcare%2FProjectAiAi/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AiAiHealthcare%2FProjectAiAi/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AiAiHealthcare%2FProjectAiAi/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/AiAiHealthcare","download_url":"https://codeload.github.com/AiAiHealthcare/ProjectAiAi/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":225533015,"owners_count":17484179,"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":["charity","convolutional-neural-networks","ct-scans","cxr-lungs","deep-learning","dicom","fda","keras","lung-cancer","lung-cancer-detection","postero-anterior","pytorch","radiologist","radiology","scikit-image","teleradiology","tensorflow","tuberculosis","x-ray"],"created_at":"2024-08-04T10:00:37.161Z","updated_at":"2024-11-20T10:30:43.380Z","avatar_url":"https://github.com/AiAiHealthcare.png","language":"Dockerfile","funding_links":[],"categories":["Code"],"sub_categories":["Repositories"],"readme":"# Project AiAi\n\n[![GitHub Commits Count](https://img.shields.io/github/commits-since/AiAiHealthcare/ProjectAiAi/0.0.svg?maxAge=300\u0026label=Github%20Commits)](https://github.com/AiAiHealthcare/ProjectAiAi/graphs/punch-card)\n\nAiAi.care project is teaching computers to \"see\" chest X-rays and interpret them how a human Radiologist would. We are using 700,000 labeled Chest X-Rays + Deep Learning to build an FDA 💊 approved, open-source screening tool for Tuberculosis and Lung Cancer. After an MRMC clinical trial, AiAi CAD will be distributed for free to emerging nations, charitable hospitals, and organizations like WHO 🌏 \n\nOur secondary goal is to open-source **'Medical Imagenet'** pretrained models and weights.  Medical data is hard to obtain, so many current Radiology-AI papers rely on transfer-learning ImageNet weights.  There are significant differences between ImageNet images (color, low-res, high-contrast) and Radiology images (grayscale, high-res, low-contrast), so we believe that our Medical Imagenet weights will improve sensitivity and specificity across the board for future research. \n\nIf you are looking for a non-technical introduction to Project AiAi, please [click here to visit https://AiAi.care website](https://AiAi.care).  In case you were wondering about the project's name, AiAi stands for _AI Augmented Imaging_.\n\n\n[![Follow Our Twitter Updates](https://img.shields.io/twitter/follow/AiAiHealthcare.svg?style=social\u0026label=Follow\u0026maxAge=3600)](https://twitter.com/AiAiHealthcare/) \n[![Join Gitter Discussion](https://img.shields.io/gitter/room/AiAi-care/Lobby.svg?maxAge=3600)](https://gitter.im/AiAi-care/Lobby) \n[![Website](https://img.shields.io/website-up-down-green-red/https/AiAi.care.svg?maxAge=3600)](https://AiAi.care/) \n\n\n# Project Milestones \nHere are [major milestones](https://github.com/AiAiHealthcare/ProjectAiAi/milestones) for the project and target completion dates:\n\n1. :white_check_mark: ~200,000 X-Ray and CT Data Loading, Cleaning _(Completed Feb 1, 2017)_\n1. :white_check_mark: Deep Learning Docker Image (**PyTorch**, HIPAA) _(Completed Feb 28, 2017 )_\n1. :white_check_mark: Data Augmentation Tests : March 30, 2017 _(Completed May 2017)_\n1. :white_check_mark: Level 1 Models : April 12, 2017 _(Completed May 2017)_\n1. :white_check_mark: HIPAA IT Audit and Validation : December 30, 2017 _(Internal Audit Completed 2017)_\n1. :white_check_mark: We got :sparkles:500,000+:sparkles: additional X-ray images! Merging this with original data. _(Completed May 2020)_\n1. :soon: Experiements with DL architectures, activations, and augmentation: _(In Progress, ETA Q1 2021)_\n1. Level 2/3 model ensembles and differential privacy (Detection, Classification) : _(In Progress, ETA Q2 2021)_\n1. Build mobile-friendly front-end for AiAi CAD (Computer Aided Detection) : Q2 2021\n1. PACS / VNA / DICOM / HL7 / EHR ingestion engine Q3 2021\n1. MRMC clinical validation for FDA application : Q3 2021\n\n\n# Donate your DL / FHIR / PACS Expertise\n\nIf you are a Machine Learning maestro, Kaggle king, or HL7 hacker then please check out our [KANBAN project tracker here](https://github.com/AiAiHealthcare/ProjectAiAi/projects/1?fullscreen=true). You can donate your time and expertise by contributing to any of the issues/tasks pinned on the KANBAN board.\n\n\n# Contribute to Legal Strategy Wiki\n\nProject AiAi is the first effort of its kind to donate an open-source, medical algorithm to the world.  This presents some interesting legal challenges, so we have [set up a wiki page where lawyers can donate their time and advice for Project AiAi.](https://github.com/AiAiHealthcare/ProjectAiAi/wiki)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FAiAiHealthcare%2FProjectAiAi","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FAiAiHealthcare%2FProjectAiAi","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FAiAiHealthcare%2FProjectAiAi/lists"}