面向决策支持的临床指南知识表示方法研究

目的：更好地表示临床指南知识,以支持临床决策支持系统的构建。方法：以缺血性卒中为例,在系统梳理临床指南知识表示方法的基础上,提出使用解释节点、数据获取节点、动作节点、复合节点,以及有向边和无向边对指南诊疗流程进行表示,同时考虑实际的电子病历数据格式,设计自然语言处理模块,提高指南与电子病历系统的数据交互能力。结果：在实证研究中,使用8个节点、7条边,以及节点和边中的4个逻辑推理式表示了缺血性卒中患者临床类型判断流程,同时使用9个节点、8条边,以及节点和边中的6个逻辑推理式表示了缺血性卒中急性期的血糖管理,详细说明了临床指南知识表示建模过程。结论：本研究提出的临床指南知识表示方法可以使用节点、边、数据、逻辑推理算法等表示临床指南知识及推理逻辑,以支撑临床决策支持系统的构建。     

联系强弱对生物医学文献知识发现的影响

分析间接关联的联系强弱在生物医学文献知识发现过程中的不同表现,明确关联性强弱对文献知识发现的影响与作用,表明通过强关联发现潜在关联的准确率显著高于由弱关联所获得的准确率,强关联性可作为提升文献知识发现应用效果的重要因素。     

面向临床决策的电子病历系统概述

电子病历系统作为医院信息化建设的核心,不仅要实现对临床信息的高效管理,还应该满足临床信息利用的需求,实现临床决策支持的功能.对国内外有关电子病历系统在临床决策支持方面的应用进行了文献综述,以求对面向临床决策的电子病历系统相关问题有较全面的了解.     

基于医疗伦理观的医疗质量成本计量与决策分析

医疗质量成本是建立在医疗伦理基础上的决策过程中或医疗服务决策时所必须考虑的一个重要因素。基于医疗伦理观的医疗信誉成本的正确计量及决策分析是医疗卫生机构提升医疗服务价值的关键所在。     

富知识发现型电子病历研发与应用进展

根据电子病历对书写灵便性、结构性、规范性的要求,分析电子签名的需求、动因、解决方案、实施效果等现状,并整合信息,提出具有丰富知识发现潜在价值的新一代电子病历系统研发模型--富知识发现型电子病历.该模型有利于从临床实践采集海量医疗信息,有利于分析、总结、挖掘和发现其中的诊疗规律与知识,进而推动临床科研一体化尤其是中医药临床研究与方法的现代化;并在提高卫生医疗保健管理与服务质量方面具有广阔前景.     

The Limitations of Decision Trees and Automatic Learning in Real World Medical Decision Making

The decision tree approach is one of the most common approaches in automatic learning and decision making. The automatic learning of decision trees and their use usually show very good results in various “ theoretical” environments. But in real life it is often impossible to find the desired number of representative training objects for various reasons. The lack of possibilities to measure attribute values, high cost and complexity of such measurements, and unavailability of all attributes at the same time are the typical representatives. For this reason we decided to use the decision trees not for their primary task—the decision making—but for outlining the most important attributes. This was possible by using a well-known property of the decision trees—their knowledge representation, which can be easily understood by humans. In a delicate field of medical decision making, we cannot allow ourselves to make any inaccurate decisions and the “tips,” provided by the decision trees, can be of a great assistance. Our main interest was to discover a predisposition to two forms of acidosis: themetabolic acidosis and respiratory acidosis, which can both have serious effects on child's health. We decided to construct different decision trees from a set of training objects. Instead of using a test set for evaluation of a decision tree, we asked medical experts to take a closer look at the generated trees. They examined and evaluated the decision trees branch by branch. Their comments show that trees generated from the available training set mainly have surprisingly good branches, but on the other hand, for some, no medical explanation could be found.     

Decision Making Based on Fuzzy Aggregation Operators for Medical Diagnosis from Dental X-ray images

Medical diagnosis is considered as an important step in dentistry treatment which assists clinicians to give their decision about diseases of a patient. It has been affirmed that the accuracy of medical diagnosis, which is much influenced by the clinicians’ experience and knowledge, plays an important role to effective treatment therapies. In this paper, we propose a novel decision making method based on fuzzy aggregation operators for medical diagnosis from dental X-Ray images. It firstly divides a dental X-Ray image into some segments and identified equivalent diseases by a classification method called Affinity Propagation Clustering (APC+). Lastly, the most potential disease is found using fuzzy aggregation operators. The experimental validation on real dental datasets of Hanoi Medical University Hospital, Vietnam showed the superiority of the proposed method against the relevant ones in terms of accuracy.     

Accuracy Enhancement in a Fuzzy Expert Decision Making System Through Appropriate Determination of Membership Functions and Its Application in a Medical Diagnostic Decision Making System

The paper attempts to improve the accuracy of a fuzzy expert decision making system by tuning the parameters of type-2 sigmoid membership functions of fuzzy input variables and hence determining the most appropriate type-1 membership function. The current work mathematically models the variability of human decision making process using type-2 fuzzy sets. Moreover, an index of accuracy of a fuzzy expert system has been proposed and determined analytically. It has also been ascertained that there exists only one rule in the rule base whose associated mapping for the ith linguistic variable maps to the same value as the maximum value of the membership function for the ith linguistic variable. The improvement in decision making accuracy was successfully verified in a medical diagnostic decision making system for renal diagnostic applications. Based on the accuracy estimations applied over a set of pathophysiological parameters, viz. body mass index, glucose, urea, creatinine, systolic and diastolic blood pressure, appropriate type-1 fuzzy sets of these parameters have been determined assuming normal distribution of type-1 membership function values in type-2 fuzzy sets. The type-1 fuzzy sets so determined have been used to develop an FPGA based smart processor. Using the processor, renal diagnosis of patients has been performed with an accuracy of 98.75%.     

基于医学知识图谱的交互式可视化医学知识服务系统

系统研究医学知识表示模型及医学知识图谱构建、语义检索和可视化分析方法,基于医学知识图谱构建交互式可视化知识服务系统,即虚拟患者,阐述技术实现方式、应用及预期成效,指出该系统有助于快速提高基层医生临床能力,减少医患矛盾。     

论医学知识创新与医学图书馆

医学知识创新既是医学科技进步的动力,又是知识经济的支撑力量.就医学知识创新系统、医学知识创新过程、对社会与经济的贡献以及医学图书馆在医学知识创新中的作用进行了讨论,并提出四点主要对策.