Mubaris Nadeem, Johannes Zenkert, Christian Weber, M. Fathi, Muhammad Hamza
{"title":"面向可穿戴救援行动的智能ux设计——紧急情况下信息检索的知识图谱信息可视化方法","authors":"Mubaris Nadeem, Johannes Zenkert, Christian Weber, M. Fathi, Muhammad Hamza","doi":"10.1109/eIT57321.2023.10187320","DOIUrl":null,"url":null,"abstract":"This paper presents a knowledge graph-informed smart UX-design approach for supporting information retrieval for a wearable, providing treatment recommendations during emergency situations to health professionals. This paper describes requirements that are unique to knowledge graph-based solutions, as well as the direct requirements of health professionals. The resulting implementation is provided for the project, which main goal is to improve first-aid rescue operations by supporting artificial intelligence in situation detection and knowledge graph representation via a contextual-based recommendation for treatment assistance.","PeriodicalId":113717,"journal":{"name":"2023 IEEE International Conference on Electro Information Technology (eIT)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Smart UX-design for Rescue Operations Wearable - A Knowledge Graph Informed Visualization Approach for Information Retrieval in Emergency Situations\",\"authors\":\"Mubaris Nadeem, Johannes Zenkert, Christian Weber, M. Fathi, Muhammad Hamza\",\"doi\":\"10.1109/eIT57321.2023.10187320\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a knowledge graph-informed smart UX-design approach for supporting information retrieval for a wearable, providing treatment recommendations during emergency situations to health professionals. This paper describes requirements that are unique to knowledge graph-based solutions, as well as the direct requirements of health professionals. The resulting implementation is provided for the project, which main goal is to improve first-aid rescue operations by supporting artificial intelligence in situation detection and knowledge graph representation via a contextual-based recommendation for treatment assistance.\",\"PeriodicalId\":113717,\"journal\":{\"name\":\"2023 IEEE International Conference on Electro Information Technology (eIT)\",\"volume\":\"94 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE International Conference on Electro Information Technology (eIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/eIT57321.2023.10187320\",\"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 International Conference on Electro Information Technology (eIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/eIT57321.2023.10187320","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Smart UX-design for Rescue Operations Wearable - A Knowledge Graph Informed Visualization Approach for Information Retrieval in Emergency Situations
This paper presents a knowledge graph-informed smart UX-design approach for supporting information retrieval for a wearable, providing treatment recommendations during emergency situations to health professionals. This paper describes requirements that are unique to knowledge graph-based solutions, as well as the direct requirements of health professionals. The resulting implementation is provided for the project, which main goal is to improve first-aid rescue operations by supporting artificial intelligence in situation detection and knowledge graph representation via a contextual-based recommendation for treatment assistance.