Hydra: a C-language environment for real-time DOS multitasking at the bedside

Patient monitoring at the bedside is an inherently parallel job, best handled by multiple individual tasks running concurrently. Cost and diffusion considerations strongly favor the use of PC's at the bedside, but their most widespread operating system, DOS, is not built for multitasking. Hence, a software platform in C language has been prepared, allowing the intermediate programmer to easily write independent modules which will then run simultaneously without conflicts.Such a platform aims at allowing effortless sharing of data among concurrently running processes, while providing strong insulation between tasks, enough to allow multiple copies of any one task to run simultaneously unknown to each other. A cooperative, memory sharing multitasking paradigm has been chosen, which offers fine granularity of timeslicing and low execution overhead at the price of some loss in generality of design.Speed, data exchange capability and number of stackable windows are greater than with commercial packages like Windows or LabWinows. Dynamical reprioritization of tasks is built in, allowing the computerized monitor to focus its attention and resources on urgent tasks.     

甲襞微循环观测辅助诊断的初步研究

甲襞微循环观测辅助诊断的初步研究胡金麟＊田牛＊刘凤英＊宋欣＊李向红＊规范化的甲襞、球结膜、舌、口唇、牙龈、耳廓、皮肤、子宫颈、阴茎头微循环观测方法标志着我国临床微循环的研究与应用已进入了一个新的阶段［１，２］。临床微循环观测结果的数学公式表达，促进了...     

运用模糊数学建立全脂乳粉卫生质量评价模型

本文运用模糊数学原理，对东台市１９９３年７月份市面上的全脂乳粉抽查监测结果进行卫生质量综合评价，结果令人满意，从而为乳粉卫生质量评比建立了客观有效的评价模型。     

用三参量模糊分析法识别潜水减压气泡信号的研究

目的 探讨潜水减压多普勒超声气泡信号的模糊识别方法。方法 根据气泡信号的频谱分布特征，构建f-f-△p三参量模糊算法，并通过减压病动物模型进行验证，同时对66例氦氧150m饱和-180m巡回潜水减压的数据进行检测。结果 在减压病动物模型中分别检测到I～Ⅱ级气泡(按Spencer分级标准)，气泡数量6～113个／3s内不等；在饱和潜水减压资料中，检测到1人两次有I级气泡音，气泡数量分别为3个(11s录音)与6个(17s录音)，与人工监听结果基本一致。结论 用三参量模糊分析方法充分借鉴了多年来人工分析所积累的经验，同时利用了计算机辅助分析技术，气泡信号的检测分析较为准确客观。     

基于灰色关联分析的中医证候推理诊断方法

针对中医诊断专家系统存在的问题,通过模拟专家诊断的思维过程,引入征候筛选和灰色关联分析模型对诊断过程进行模拟和评价,实现了一个新的计算机化中医诊断方法。     

化合物构效关系的模糊极小极大神经网络识别研究

应用模糊极小极大神经网络研究了化合物复杂结构和性能（QSAR）之间的关系，用该法进行几组化合物致癌的识别，结果优于线性回归的方法，对此作出一些分析。     

模糊ART神经网络在心律失常分析中的应用

本研究提出一种用模糊ART神经网络进行心律失常分析的方法。确定用于描述QRS波群特征的若干属性 ,提取其特征 ,模糊化处理后作为神经网络的输入模式矢量。神经网络为三层结构 ,经过竞争学习 ,对QRS波群进行自动分类。分类结果用MIT -BIH数据库进行了检验 ,证明本方法非常有效 ,30min数据的分析时间小于 2s,满足实用要求     

Fuzzy rules to predict degree of malignancy in brain glioma

The current pre-operative assessment of the degree of malignancy in brain glioma is based on magnetic resonance imaging (MRI) findings and clinical data. 280 cases were studied, of which 111 were high-grade malignancies and 169 were low-grade, so that regular and interpretable patterns of the relationships between glioma MRI features and the degree of malignancy could be acquired. However, as uncertainties in the data and missing values existed, a fuzzy rule extraction algorithm based on a fuzzy min-max neural network (FMMNN) was used. The performance of a multi-layer perceptron network (MLP) trained with the error back-propagation algorithm (BP), the decision tree algorithm ID3, nearest neighbour and the original fuzzy min-max neural network were also evaluated. The results showed that two fuzzy decision rules on only six features achieved an accuracy of 84.6% (89.9% for low-grade and 76.6% for high-grade cases). Investigations with the proposed algorithm revealed that age, mass effect, oedema, post-contrast enhancement, blood supply, calcification, haemorrhage and the signal intensity of the T1-weighted image were important diagnostic factors.     

Microcomputer-based automatic regulation of extracorporeal circulation: a trial for the application of fuzzy inference

Since its establishment many researchers have been trying to automate the process of extracorporeal circulation (ECC). We developed a preliminary experimental model of an automatic regulatory system for ECC. The purpose of the system was to regulate basic hemodynamic parameters such as pump flow and withdrawal blood volume. It was divided into three main components: data sampling unit, central processing unit, and controlling unit. Based on this model we were able to achieve autoregulation of ECC using minimum configuration; however, the system lacked smoothness. This was partly because it was based on a "static" regulation system which used conditional statements having multiple parameters. In this study, we applied fuzzy logic to the former model to achieve more accurate and reliable regulation. We report experimental results for the new system and compare the data between clinical circulation in 13 infants (mean body weight, 13.32 +/- 5.99 kg) and experimental regulation in 7 mongrel dogs (mean body weight, 11.9 +/- 2.53 kg). The comparative study revealed no statistical difference between the two groups. This result suggests that the automatic regulation of ECC may be an alternative to manual operation by a professional perfusionist in the near future.     

基于伪F统计量的模糊聚类方法在医疗质量综合评价中的应用

目的探讨一种新的基于伪F统计量的最佳聚类分析方法,该方法不需要预先选择类的数目作为先验值.并有效地应用于医疗质量的综合评价.方法首先,应用FCM模糊聚类法(Fuzzy Clustering Method)进行聚类,然后应用PFS(Pseudo F-statistics)统计量作为一个判别函数来确定最佳类数目.结果将该方法应用于某院2002年度各科室医疗质量综合评价,得到了一种合理的综合评价结果.结论该方法基于没有聚类数据的任何先验知识和组成成分信息的前提下,考虑如何确定数据的分类结构.根据应用的情况,发现该方法是医疗质量综合评价的有力工具.