A distributed adverse drug reaction detection system using intelligent agents with a fuzzy recognition‐primed decision model

Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is highly desirable. Nevertheless, current postmarketing surveillance methods largely rely on spontaneous reports that suffer from serious underreporting, latency, and inconsistent reporting. Thus these methods are not ideal for rapidly identifying rare ADRs. The multiagent systems paradigm is an emerging and effective approach to tackling distributed problems, especially when data sources and knowledge are geographically located in different places and coordination and collaboration are necessary for decision making. In this article, we propose an active, multiagent framework for early detection of ADRs by utilizing electronic patient data distributed across many different sources and locations. In this framework, intelligent agents assist a team of experts based on the well‐known human decision‐making model called Recognition‐Primed Decision (RPD). We generalize the RPD model to a fuzzy RPD model and utilize fuzzy logic technology to not only represent, interpret, and compute imprecise and subjective cues that are commonly encountered in the ADR problem but also to retrieve prior experiences by evaluating the extent of matching between the current situation and a past experience. We describe our preliminary multiagent system design and illustrate its potential benefits for assisting expert teams in early detection of previously unknown ADRs. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 827–845, 2007.     

Neural networks and blood cell identification

The objective of this project is to propose a method of identifying cells found in human blood and to classify them based upon their morphological features using neural networks. The project focuses on three major blood cell types, namely, erythrocytes, leukocytes and platelets. The data are collected using peripheral blood smears from clinical patients. The image acquisition requires 100x magnification on all the blood smears, the preprocessing involves the use of median and edge enhance filters; the feature extraction is done by performing the wavelet transform on the images. Finally classification of the blood cell types is done using ALOPEX and Back Propagation trained neural networks. The efficacy of both networks is then compared by comparing their outputs and number of iterations required to reach the final result.     

O—O数据模型中实体联系的表达方法

具有对实体和实体间联系的描述能力，是数据库的基本，吼是对数据库进逻辑设计的基本出发点。Ｏ－Ｏ数据模型不具备显式描术这实体联系的手段。且优于关系模型。     

改善磁盘阵列性能的方法

磁盘阵列是解决计算机Ｉ／Ｏ瓶颈问题的有效方法之一，通过对现有磁盘阵列结构的研究，提出了４种改善磁盘阵列性能的方法，即良分利用磁盘带宽，平衡多盘的负载，减少奇偶检验数据存取时间和磁盘阵列Ｃａｃｈｅ技术等，分析结果表明：在事务处理应用领域，利用Ｃａｃｈｅ来把小写转化为大写可大大改善目前一般情况下，以一道数据大小来作为磁盘的基本存取大小是合适的选择，磁盘阵列负载平衡设计不足是指正常模式下系统请求在多盘间     

氧化铝/锌合金复合材料界面的SEM观察

利用挤压铸造制备氧化铝／锌合金复合材料，在扫描电镜（ＳＥＭ）上观察复合材料的界面。结果表明，在复合材料中纤维与基体间存在致密界面层，合金元素通过适当的化学反应可改善纤维与基体间的结合；在凝固过程中，纤维／基体界面上的硅在共晶体的共生生长过程中起了领先相作用，导致复合材料的共晶转变是由铝硅共晶转变和锌铝共晶转变两者组成。     

用Calyculin A诱导的染色体凝聚研究辐射的剂量效应关系

采用不同剂量（0，0.25,0.5,1.0,2.0,3.0Gy)的60Coγ射线照射离体人血，于照后46h加入CalyculinA，观察其诱导的染色体凝聚，并与常规染色体畸变法进行比较，结果表明，Calyculin A法PCC与常规秋水仙素阻滞法及融合法PCC相比可获得更高的分裂指数，Calyculin A法PCC的断片数与剂量之间呈良好的线性关系。     

一种简便的评定引战配合效率方法

在导弹近炸引信起爆延时具有随机性基础上，本文建立了一种用延时及其数学特征表示的评定引战配合效率的简便方法，并对有关应用问题进行了讨论。