Bellika Johan Gustav, Hartvigsen Gunnar
Norwegian Centre for Telemedicine, University Hospital of North Norway, N-9038 Tromsø, Norway.
Int J Med Inform. 2005 Aug;74(7-8):587-95. doi: 10.1016/j.ijmedinf.2005.06.001.
When a person gets a cancer diagnosis the need for medical guidance often appears. In Norway, one of the providers of medical guidelines is the Norwegian Cancer Association where oncological nurses assist people with a cancer diagnosis or their relatives. The nurses search through both national and internal guidebooks and web pages. The input to this process is mostly discharge letters. The whole process is time consuming. To serve more patients, PaSent, a web-based intelligent oncological nurse advisor, has been developed. Through using discharge letters as input to our neural network-based information retrieval system PaSent, we have been able to provide relevant medical information to the patient as well as to the health personnel themselves. The PaSent search method uses predefined knowledge about the context, paired with the vocabulary of the input document, to compute a relevance measure for a potential result document. The system has been validated by oncological nurses and medical doctors. In the reported experiments, the PaSent system is able to recommend literature, in the top section of the search result list, that our judges also found highly relevant.
当一个人被诊断出患有癌症时，通常就会需要医疗指导。在挪威，医疗指南的提供者之一是挪威癌症协会，肿瘤护理人员会为癌症确诊患者或其亲属提供帮助。这些护士会查阅国家和内部的指南手册以及网页。这个过程的输入主要是出院小结。整个过程很耗时。为了服务更多患者，已经开发了一个基于网络的智能肿瘤护理顾问PaSent。通过将出院小结作为基于神经网络的信息检索系统PaSent的输入，我们能够为患者以及医护人员自身提供相关的医疗信息。PaSent搜索方法使用关于上下文的预定义知识，并结合输入文档的词汇，来计算潜在结果文档的相关性度量。该系统已经得到肿瘤护理人员和医生的验证。在报告的实验中，PaSent系统能够在搜索结果列表的顶部推荐文献，我们的评审人员也认为这些文献高度相关。
