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src=\"https://img.shields.io/badge/Documentation-FFCD00?style=for-the-badge\u0026logo=data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIGhlaWdodD0iMjQiIHZpZXdCb3g9IjAgLTk2MCA5NjAgOTYwIiB3aWR0aD0iMjQiPjxwYXRoIGQ9Ik0zMjAtMjQwaDMyMHYtODBIMzIwdjgwWm0wLTE2MGgzMjB2LTgwSDMyMHY4MFpNMjQwLTgwcS0zMyAwLTU2LjUtMjMuNVQxNjAtMTYwdi02NDBxMC0zMyAyMy41LTU2LjVUMjQwLTg4MGgzMjBsMjQwIDI0MHY0ODBxMCAzMy0yMy41IDU2LjVUNzIwLTgwSDI0MFptMjgwLTUyMHYtMjAwSDI0MHY2NDBoNDgwdi00NDBINTIwWk0yNDAtODAwdjIwMC0yMDAgNjQwLTY0MFoiLz48L3N2Zz4=\"/\u003e\u003c/a\u003e\n  \u003ca href=\"https://asreview.app\"\u003e\u003cimg src=\"https://img.shields.io/badge/Live_Demo-C00A35?style=for-the-badge\u0026logo=data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIGhlaWdodD0iMjQiIHZpZXdCb3g9IjAgLTk2MCA5NjAgOTYwIiB3aWR0aD0iMjQiPjxwYXRoIGQ9Ik0yMDAtMTIwcS0zMyAwLTU2LjUtMjMuNVQxMjAtMjAwdi01NjBxMC0zMyAyMy41LTU2LjVUMjAwLTg0MGg1NjBxMzMgMCA1Ni41IDIzLjVUODQwLTc2MHY1NjBxMCAzMy0yMy41IDU2LjVUNzYwLTEyMEg2MDB2LTgwaDE2MHYtNDgwSDIwMHY0ODBoMTYwdjgwSDIwMFptMjQwIDB2LTI0NmwtNjQgNjQtNTYtNTggMTYwLTE2MCAxNjAgMTYwLTU2IDU4LTY0LTY0djI0NmgtODBaIi8+PC9zdmc+\u0026logoColor=white\"/\u003e\u003c/a\u003e\n\u003c/p\u003e\n\u003c/br\u003e\n\n## ASReview LAB: Active Learning for Systematic Reviews\n\n**ASReview LAB** is an open-source machine learning tool for efficient,\ntransparent, and interactive screening of large textual datasets. It is widely\nused for systematic reviews, meta-analyses, and any scenario requiring\nsystematic text screening.\n\nThe key features of **ASReview LAB** are:\n\n- **Active Learning**: Interactively prioritize records using AI models that\n  learn from your labeling decisions.\n- **Scientifically validated**: ASReview LAB has been scientifically validated\n  and published in [Nature Machine\n  Intelligence](https://doi.org/10.1038/s42256-020-00287-7).\n- **Flexible AI Models**: Choose from pre-configured ELAS models or build your\n  own with custom components.\n- **Simulation toolkit**: Assess model performance on fully labeled datasets.\n- **Label Management**: All decisions are saved automatically; easily change\n  labels at any time.\n- **User-Centric Design**: Humans are the oracle; the interface is transparent\n  and customizable.\n- **Privacy First**: Everything is open source and no usage or user data is\n  collected.\n\n---\n\n### What's New in Version 3?\n\n- **Automatic Duplicate Hiding**: Records with duplicate titles and texts are\n  automatically hidden during screening, keeping your workflow clean and tidy.\n  Need those records back? No problem — you can choose to include them when you\n  export your data.\n- **Editable Tags in Collection**: Manage and edit tags directly from the\n  Collection screen, giving you more control over your data extraction and classification.\n\n---\n\n## Installation\n\nRequires Python 3.10 or later.\n\n```bash\npip install asreview\n```\n\nUpgrade:\n\n```bash\npip install --upgrade asreview\n```\n\nFor Docker and advanced installation, see the [installation\nguide](https://asreview.readthedocs.io/en/stable/lab/installation.html).\n\nLatest version of ASReview LAB: [![PyPI\nversion](https://badge.fury.io/py/asreview.svg)](https://badge.fury.io/py/asreview)\n\n\n\n## The ASReview LAB Workflow\n\n1. **Import Data**: Load your dataset (CSV, RIS, XLSX, etc.).\n2. **Create Project**: Set up a new review or simulation project.\n3. **Select Prior Knowledge**: Optionally provide records you already know are\n   relevant or not relevant.\n4. **Start Screening**: Label records as Relevant or Not Relevant; the AI model\n   continuously improves.\n5. **Monitor Progress**: Use the dashboard to track your progress and decide\n   when to stop.\n6. **Export Results**: Download your labeled dataset or project file.\n\n[![ASReview\nLAB](https://github.com/asreview/asreview/blob/main/images/ASReviewWebApp.png?raw=true)](https://asreview.readthedocs.io/en/stable/lab/about.html\n\"ASReview LAB\")\n\n---\n\n## Documentation \u0026 Resources\n\n- [Documentation](https://asreview.readthedocs.io/)\n- [Video tutorials](https://www.youtube.com/@ASReview)\n- [AI models of ASReview\n  LAB](https://asreview.readthedocs.io/en/latest/lab/models.html)\n- [FAQ](https://github.com/asreview/asreview/discussions?discussions_q=sort%3Atop)\n- [Live Demo](https://asreview.app)\n\n\n## Citation\n\nIf you wish to cite the underlying methodology of the ASReview software, please\nuse the following publication in Nature Machine Intelligence:\n\n\u003e van de Schoot, R., de Bruin, J., Schram, R. et al. An open source machine\n\u003e learning framework for efficient and transparent systematic reviews. Nat Mach\n\u003e Intell 3, 125–133 (2021). https://doi.org/10.1038/s42256-020-00287-7\n\nFor citing the software, please refer to the specific release of the ASReview\nsoftware on Zenodo: https://doi.org/10.5281/zenodo.3345592. The menu on the\nright can be used to find the citation format you need.\n\nFor more scientific publications on the ASReview software, go to\n[asreview.ai/papers](https://asreview.ai/papers/).\n\n## Community \u0026 Contact\n\nThe best resources to find an answer to your question or ways to get in contact\nwith the team are:\n\n- [Newsletter](https://asreview.ai/newsletter/subscribe)\n- [FAQ](https://github.com/asreview/asreview/discussions?discussions_q=sort%3Atop)\n- [Community events](https://asreview.ai/events)\n- [Issues or feature requests](https://github.com/asreview/asreview/issues)\n- [Donate to ASReview](https://asreview.ai/donate)\n- [Contact](mailto:asreview@uu.nl) (asreview@uu.nl)\n\n## License\n\nThe ASReview software has an Apache 2.0 [LICENSE](LICENSE). The ASReview team\naccepts no responsibility or liability for the use of the ASReview tool or any\ndirect or indirect damages arising out of the application of the tool.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fasreview%2Fasreview","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fasreview%2Fasreview","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fasreview%2Fasreview/lists"}