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Collection of Medical Original Data with Search Engine for Decision Support

机译:使用搜索引擎收集医疗原始数据,用于决策支持

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Medicine is becoming more and more complex and humans can capture total medical knowledge only partially. For specific access a high resolution search engine is demonstrated, which allows besides conventional text search also search of precise quantitative data of medical findings, therapies and results. Users can define metric spaces ('Domain Spaces", DSs) with all searchable quantitative data ("Domain Vectors", DSs). An implementation of the search engine is online in http://numericsearch.com . In future medicine the doctor could make first a rough diagnosis and check which fine diagnostics (quantitative data) colleagues had collected in such a case. Then the doctor decides about fine diagnostics and results are sent (half automatically) to the search engine which filters a group of patients which best fits to these data. In this specific group variable therapies can be checked with associated therapeutic results, like in an individual scientific study for the current patient. The statistical (anonymous) results could be used for specific decision support. Reversely the therapeutic decision (in the best case with later results) could be used to enhance the collection of precise pseudonymous medical original data which is used for better and better statistical (anonymous) search results.
机译:医学变得越来越复杂,人类可以仅部分地捕获医学知识。对于特定访问,证明了高分辨率搜索引擎,其允许除传统的文本搜索外,还允许搜索医学发现,治疗和结果的精确定量数据。用户可以使用所有可搜索的定量数据(“域向量”,DSS)定义度量空间(“域空间”,DSS)。搜索引擎的实现在http:/numericsearch.com中在线。在未来医学中,医生可以首先是在这种情况下收集的粗略诊断和检查哪些精细诊断(定量数据)同事。然后医生决定了精细的诊断,结果被发送到搜索引擎(一半)滤除一组最适合的一组患者对这些数据。在该特定的组中,可以用相关的治疗结果检查变量疗法,如在当前患者的个人科学研究中。统计(匿名)结果可用于具体决策支持。反转治疗决策(在稍后的结果最佳案例)可用于增强用于更好且更好的统计(匿名)搜索重新的精确伪医疗原始数据的集合TS。

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