An optimal tumor marker group-coupled artificial neural network for diagnosis of lung cancer

BackgroundEpidemiological statistics has shown that there are approximately 1.2 million new cases of lung cancer diagnosed every year and the death rate of these patients is 17.8%. Earlier diagnosis is key to promote the five-year survival rate of these cancer patients. Some tumor markers have been found to be valuable for earlier diagnosis, but a single marker has limitation in its sensitivity and specificity of cancer diagnosis. To improve the efficiency of diagnosis, several distinct tumor marker groups are combined together using a mathematical evaluation model, called artificial neural network (ANN). Lung cancer markers have been identified to include carcinoembryonic antigen, carcinoma antigen 125, neuron specific enolase, β₂-microglobulin, gastrin, soluble interleukin-6 receptor, sialic acid, pseudouridine, nitric oxide, and some metal ions.MethodsThese tumor markers were measured through distinct experimental procedures in 50 patients with lung cancer, 40 patients with benign lung diseases, and 50 cases for a normal control group. The most valuable were selected into an optimal tumor marker group by multiple logistic regression analysis. The optimal marker group-coupled ANN model was employed as an intelligent diagnosis system.ResultsWe have presented evidence that this system is superior to a traditional statistical method, its diagnosis specificity significantly improved from 72.0% to 100.0% and its accuracy increased from 71.4% to 92.8%.ConclusionsThe ANN-based system may provide a rapid and accurate diagnosis tool for lung cancer.     

基于 ICEEMDAN-MSE 的左室舒张功能 障碍心音信号的识别研究

左室舒张功能障碍(LVDD)加重会导致左室重构、室壁僵硬、顺应性降低，从而走向不可逆阶段并进展为射血分数保留型心力衰竭。为早期诊断LVDD,本文提出一种基于改进的自适应噪声完全集合经验模式分解(ICEEMDAN)多尺度样本熵(MSE)的心音特征结合逻辑回归模型的无创检测方法。首先，采用改进的小波去噪方法对心音信号进行预处理。其次，通过ICEEMDAN方法将非平稳的心音信号分解为多个反映心音本体特征的平稳的固有模态函数(IMF),再利用互相关系数准则筛选IMF,并提取所筛选IMF的MSE,以构成特征向量作为分类器的输入。最后，通过与其他3种分类模型的性能比较，将逻辑回归应用于LVDD识别。结果表明，该方法能有效提取心音特征，其准确率为89.85%,灵敏度为92.17%,特异度为87.63%,证明了采用心音信号对LVDD进行早期诊断的有效性。     

The Trellis security infrastructure for overlay metacomputers and bridged distributed file systems

Researchers often have non-privileged access to a variety of high-performance computer (HPC) systems in different administrative domains, possibly across a wide-area network. Consequently, the security infrastructure becomes an important component of an overlay metacomputer: a user-level aggregation of HPC systems.The Trellis security infrastructure (TSI) is layered on top of the widely-deployed secure shell (SSH) and systems administrators only need to provide unprivileged accounts to the users. The contribution of TSI is in demonstrating that a single sign-on (SSO) system, for a variety of use-case scenarios, can be implemented without requiring a completely new security infrastructure. We describe the use of TSI for a Canada-wide overlay metacomputer, for computational workloads (i.e., CISS-3) that spanned 22 administrative domains, at its peak had over 4000 concurrent jobs, and included a new distributed file system (i.e., Trellis NFS).     

特征迁移结合主动标注的颅内病变鉴别方法

为了解决使用磁共振图像进行脑炎和胶质瘤的临床诊断时会出现误诊的问题,提出了一种卷积层特征迁移结合主动样本标注的分类方法.该方法首先采用卷积层特征参数迁移,利用磁共振成像(MRI)数据进行模型的微调,并验证了不同MRI模态特征的区分能力;其次针对样本标注困难问题,设计基于熵不确定性的样本主动标注算法,提取样本的不确定性信息,进一步提高模型的收敛速度以及泛化能力.在由重庆医科大学附属第一医院放射科纳入的175个病例(脑炎118例,胶质瘤57例)上进行实验,在交叉验证下分类准确率达到95.08％,曲线下面积达到0.98,模型的分类精度显著优于现阶段主要依靠医生经验的方法,准确率和曲线下面积分别提高17.51％和0.15;同时仅需要标注30％的数据样本,模型便能达到最优性能,减少大量数据标注工作,能够为初期诊断提供有意义的指导.     

基于改进导向滤波算法的低剂量CT图像处理

导向滤波算法是一种有效的基于边保持的平滑滤波算法.然而,由于算法中的正则化系数和细节层增益是固定的,可能会导致边附近出现光晕以及背景中出现大量噪声,降低图像的质量.在本文中,首先给出了一种改进的基于边的权重系数计算方法,它能够较准确地实现边保持,减少光晕现象.其次,提出了基于梯度导向的细节层增益计算方法,可以有效地增强细节并且抑制噪声.实验表明,对于含有大量噪声和小细节的低剂量CT图像,本文方法可以减少噪声和光晕的影响,显著提高图像的对比度,满足临床诊断的需要.     

A new form of accelerator for charged particles

A new form of accelerator is proposed which employs an electric field of constant magnitude rotating in a plane perpendicular to a static magnetic guidance field.     

The relative success of alternative approaches to strategic information systems planning: an empirical analysis

Strategic information systems planning (SISP) is an exercise or ongoing activity that enables organisations to develop priorities for information systems development. It has been suggested that the ‘SISP approach’, a combination of method, process and implementation, is the most complete way of describing SISP activity. Based upon questionnaire responses from 267 IT Directors, four distinct approaches to SISP have been derived using cluster analysis. A comparison of these four approaches with five approaches of Earl, M.J., 1993. Experiences in SISP, MIS Quarterly, (March), 1–24, indicates that three bear strong similarities to the ‘organisational’, ‘business-led’, and ‘administrative’ approaches, whilst the fourth cluster is related to both Earl's ‘method-driven’ and ‘technological’ approaches. An analysis of the relationship between SISP approach and SISP success demonstrates that the ‘organisational approach’ is significantly more successful than the other three approaches.