{"title":"人工智能生活实验室:基于人工智能的卫生系统的质量保证","authors":"Valentina Lenarduzzi, M. Isomursu","doi":"10.1109/CAIN58948.2023.00018","DOIUrl":null,"url":null,"abstract":"The main goal of this project is to develop an AI Living Lab providing methods and software tools for AI trustworthiness analysis, running digital twins to simulate Digital Health solutions (Hardware and Software) integrated with AI elements in vitro for early-stage validation experiments. In this paper, we present the motivation beyond the need of a AI Living Lab methods for researchers and companies, our idea in practice, and the scheduled roadmap. The insights of the AI Living Lab can enable researchers to understand possible problems on the quality of AI-enabled systems opening new research topics and allows companies to understand how to better address quality issues in their systems.","PeriodicalId":175580,"journal":{"name":"2023 IEEE/ACM 2nd International Conference on AI Engineering – Software Engineering for AI (CAIN)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AI Living Lab: Quality Assurance for AI-based Health systems\",\"authors\":\"Valentina Lenarduzzi, M. Isomursu\",\"doi\":\"10.1109/CAIN58948.2023.00018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The main goal of this project is to develop an AI Living Lab providing methods and software tools for AI trustworthiness analysis, running digital twins to simulate Digital Health solutions (Hardware and Software) integrated with AI elements in vitro for early-stage validation experiments. In this paper, we present the motivation beyond the need of a AI Living Lab methods for researchers and companies, our idea in practice, and the scheduled roadmap. The insights of the AI Living Lab can enable researchers to understand possible problems on the quality of AI-enabled systems opening new research topics and allows companies to understand how to better address quality issues in their systems.\",\"PeriodicalId\":175580,\"journal\":{\"name\":\"2023 IEEE/ACM 2nd International Conference on AI Engineering – Software Engineering for AI (CAIN)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE/ACM 2nd International Conference on AI Engineering – Software Engineering for AI (CAIN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAIN58948.2023.00018\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE/ACM 2nd International Conference on AI Engineering – Software Engineering for AI (CAIN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAIN58948.2023.00018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
AI Living Lab: Quality Assurance for AI-based Health systems
The main goal of this project is to develop an AI Living Lab providing methods and software tools for AI trustworthiness analysis, running digital twins to simulate Digital Health solutions (Hardware and Software) integrated with AI elements in vitro for early-stage validation experiments. In this paper, we present the motivation beyond the need of a AI Living Lab methods for researchers and companies, our idea in practice, and the scheduled roadmap. The insights of the AI Living Lab can enable researchers to understand possible problems on the quality of AI-enabled systems opening new research topics and allows companies to understand how to better address quality issues in their systems.
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