首页> 外文会议>International work-conference on the interplay between natural and artificial computation >Abstracting Classification Models Heterogeneity to Build Clinical Group Diagnosis Support Systems
【24h】

Abstracting Classification Models Heterogeneity to Build Clinical Group Diagnosis Support Systems

机译:抽象分类模型的异质性以建立临床群体诊断支持系统

获取原文

摘要

Many diagnosis support systems (DSS) are focused on precise disorders, being not useful for differential diagnosis (DD) or facing comorbidities. Few DSSs offer a rich list of potential diagnoses and they do not reflect complex relations between diseases to be diagnosed. We present a model to allow collaboration of multiple heterogeneous diagnostic units (DU), which are actual DSSs, behaving as a whole system. The heterogeneity of the DUs refers to the disease they diagnose and the classification model they use to do so. This model offers a framework to build multi-purpose DSSs, assuring their operability and functioning despite the heterogeneity of the single diagnostic units.
机译:许多诊断支持系统(DSS)专注于精确的疾病,对于鉴别诊断(DD)或面临合并症没有用。几乎没有DSS提供丰富的潜在诊断清单,并且它们不能反映出要诊断的疾病之间的复杂关系。我们提出了一个模型,以允许多个异类诊断单元(DU)协同工作,它们是实际的DSS,具有整个系统的性能。 DU的异质性指的是他们诊断出的疾病以及用于诊断的分类模型。该模型提供了构建多功能DSS的框架,尽管单个诊断单元具有异质性,但仍可确保其可操作性和功能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号