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| Hauptverfasser: | , , , , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2509.25434 |
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| _version_ | 1866908606154145792 |
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| author | Ferreira, Ana Paula Gomes Anžel, Aleksandar de Souza, Izabel Oliva Marcilio Hughes, Helen Elliot, Alex J Kong, Jude Dzevela Schranz, Madlen Ullrich, Alexander Hattab, Georges |
| author_facet | Ferreira, Ana Paula Gomes Anžel, Aleksandar de Souza, Izabel Oliva Marcilio Hughes, Helen Elliot, Alex J Kong, Jude Dzevela Schranz, Madlen Ullrich, Alexander Hattab, Georges |
| contents | Case definitions are essential for effectively communicating public health threats. However, the absence of a standardized, machine-readable format poses significant challenges to interoperability, epidemiological research, the exchange of qualitative data, and the effective application of computational analysis methods, including artificial intelligence (AI). This complicates comparisons and collaborations across organizations and regions, limits data integration, and hinders technological innovation in public health. To address these issues, we propose the first open, machine-readable format for representing case and syndrome definitions. Additionally, we introduce the first comprehensive dataset of standardized case definitions and tools to convert existing human-readable definitions into machine-readable formats. We also provide an accessible online platform for browsing, analyzing, and contributing new definitions, available at https://opensyndrome.org. The Open Syndrome Definition format enables consistent, scalable use of case definitions across systems, unlocking AI's potential to strengthen public health preparedness and response. The source code for the format can be found at https://github.com/OpenSyndrome/schema under the MIT license. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_25434 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The Open Syndrome Definition Ferreira, Ana Paula Gomes Anžel, Aleksandar de Souza, Izabel Oliva Marcilio Hughes, Helen Elliot, Alex J Kong, Jude Dzevela Schranz, Madlen Ullrich, Alexander Hattab, Georges Artificial Intelligence Case definitions are essential for effectively communicating public health threats. However, the absence of a standardized, machine-readable format poses significant challenges to interoperability, epidemiological research, the exchange of qualitative data, and the effective application of computational analysis methods, including artificial intelligence (AI). This complicates comparisons and collaborations across organizations and regions, limits data integration, and hinders technological innovation in public health. To address these issues, we propose the first open, machine-readable format for representing case and syndrome definitions. Additionally, we introduce the first comprehensive dataset of standardized case definitions and tools to convert existing human-readable definitions into machine-readable formats. We also provide an accessible online platform for browsing, analyzing, and contributing new definitions, available at https://opensyndrome.org. The Open Syndrome Definition format enables consistent, scalable use of case definitions across systems, unlocking AI's potential to strengthen public health preparedness and response. The source code for the format can be found at https://github.com/OpenSyndrome/schema under the MIT license. |
| title | The Open Syndrome Definition |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2509.25434 |