放射学中心搜索引擎设计与临床验证的现代非SQL方法
A Modern Non-SQL Approach to Radiology-Centric Search Engine Design with Clinical Validation
摘要：
医疗保健数据的规模正以前所未有的速度增长，人们非常关注大数据分析和人工智能应用，以用于质量保证、临床培训、严重程度分类和决策支持。放射学非常适合创新，因为它固有地配对了语言和视觉数据。以前试图打开这个信息金矿的尝试受到人类语言的异质性，专有搜索算法以及缺乏医学特定搜索性能矩阵的阻碍。我们提出了一个从头开始的过程中开发一个基于文档的，安全的，高效的，准确的搜索引擎的背景下，放射学。我们评估我们的实施搜索引擎与比较预先存在的手动收集的临床数据库，以前用于临床研究项目，除了计算性能基准和调查反馈。通过利用高效的数据库架构、搜索功能和临床思维，放射科医生处于利用医疗保健数据的最前沿。
英文摘要：
Healthcare data is increasing in size at an unprecedented speed with much attention on big data analysis and Artificial Intelligence application for quality assurance, clinical training, severity triaging, and decision support. Radiology is well-suited for innovation given its intrinsically paired linguistic and visual data. Previous attempts to unlock this information goldmine were encumbered by heterogeneity of human language, proprietary search algorithms, and lack of medicine-specific search performance matrices. We present a de novo process of developing a document-based, secure, efficient, and accurate search engine in the context of Radiology. We assess our implementation of the search engine with comparison to pre-existing manually collected clinical databases used previously for clinical research projects in addition to computational performance benchmarks and survey feedback. By leveraging efficient database architecture, search capability, and clinical thinking, radiologists are at the forefront of harnessing the power of healthcare data.
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