Present work was designed to quantitatively evaluate the performance of diffusion-weighted magnetic resonance imaging（DWI） in the diagnosis of the presence of metastasis in lymph nodes（LNs）. Eligible studies were ...Present work was designed to quantitatively evaluate the performance of diffusion-weighted magnetic resonance imaging（DWI） in the diagnosis of the presence of metastasis in lymph nodes（LNs）. Eligible studies were identified from systematical Pub Med and EMBASE searches. Data were extracted. Meta-analyses were performed to generate pooled sensitivity and specificity on the basis of per-node, per-lesion and per-patient, respectively. Fourteen publications（2458 LNs, 404 lesions and 334 patients） were eligible. Per-node basis demonstrated the pooled sensitivity and specificity was 0.82（P〈0.0001） and 0.90（P〈0.0001）, respectively. Per-lesion basis illustrated the pooled sensitivity and specificity was 0.73（P=0.0036） and 0.85（P〈0.0001）, respectively. Per-patient basis indicated the pooled sensitivity and specificity was 0.67（P=0.0909） and 0.86（P〈0.0001）, respectively. In conclusion, DWI has rather a negative predictive value for the diagnosis of LN metastasis presence. The difference of the mean apparent diffusion coefficients between benign and malignant LNs is not yet stable. Therefore, the DWI technique has to be further improved.展开更多
Node of network has lots of information, such as topology, text and label information. Therefore, node classification is an open issue. Recently, one vector of node is directly connected at the end of another vector. ...Node of network has lots of information, such as topology, text and label information. Therefore, node classification is an open issue. Recently, one vector of node is directly connected at the end of another vector. However, this method actually obtains the performance by extending dimensions and considering that the text and structural information are one-to-one, which is obviously unreasonable. Regarding this issue, a method by weighting vectors is proposed in this paper. Three methods, negative logarithm, modulus and sigmoid function are used to weight-trained vectors, then recombine the weighted vectors and put them into the SVM classifier for evaluation output. By comparing three different weighting methods, the results showed that using negative logarithm weighting achieved better results than the other two using modulus and sigmoid function weighting, and was superior to directly concatenating vectors in the same dimension.展开更多
Malignant melanoma is a malignancy of pigmentproducing cells(melanocytes) located predominantly in the skin. Nodal metastases are an adverse prognostic factor compromising long term patient survival. Therefore, accura...Malignant melanoma is a malignancy of pigmentproducing cells(melanocytes) located predominantly in the skin. Nodal metastases are an adverse prognostic factor compromising long term patient survival. Therefore, accurate detection of regional nodal metastases is required for optimization of treatment. Computed tomography(CT) and magnetic resonance imaging(MRI) remain the primary imaging modalities for regional staging of malignant melanoma. However, both modalities rely on size-related and morphological criteria to differentiate between benign and malignant lymph nodes, decreasing the sensitivity for detection of small metastases. Surgery is the primary mode of therapy for localized cutaneous melanoma. Patients should be followed up for metastases after surgical removal. We report here a case of inguinal lymph node enlargement with a genital vesicular lesion with a history of surgery for malignant melanoma on her thigh two years ago. CT and diffusion weighted-MRI(DW-MRI) were applied for the lymph node identification. DW-MRI revealed malignant lymph nodes due to malignant melanoma metastases correlation with pathological findings.展开更多
【目的】地球表层系统科学数据有向加权关联网络的关键节点识别对科学数据精准推荐与知识发现具有重要意义,但现有方法存在评估片面、特征利用不足及权重分配科学性欠缺等挑战。【方法】本文提出一种基于主客观融合权重的逼近理想解排序...【目的】地球表层系统科学数据有向加权关联网络的关键节点识别对科学数据精准推荐与知识发现具有重要意义,但现有方法存在评估片面、特征利用不足及权重分配科学性欠缺等挑战。【方法】本文提出一种基于主客观融合权重的逼近理想解排序法(Technique for Order Preference by Similarity to an Ideal Solution, TOPSIS)的关键节点识别方法。首先,提出节点相似中心性指标,通过融合关联度与强度平衡局部拓扑与全局影响力;然后,构建整合网络拓扑、数据关联及节点相似性的多指标评价体系,全面刻画节点重要性;接着,提出双层权重优化策略,结合层次分析法(Analytic Hierarchy Process, AHP)和指标相关性定权法(Criteria Importance Through Intercriteria Correlation, CRITIC)方法,融合主客观权重,提升评估科学性;最后,结合TOPSIS评估方法进行节点重要性的综合评估。【结果】实验基于团队构建的不同规模的地表系统科学数据有向加权关联网络,结合加权易感-感染-恢复(SIR)模型进行实验验证,结果表明:与传统网络加权中心性以及基于主观或客观权重的TOPSIS等方法相比,本文方法在肯德尔相关系数值和TOP-K命中率方面表现更优,且在网络中展现强鲁棒性。【结论】该方法为地表系统科学数据网络分析提供了新方法,可支撑智能推荐、资源优化及系统脆弱性分析等实际应用,助力地球系统科学研究的深度发展。展开更多
配电网中关键节点与主干线路的失效可能引发电网大规模故障,对供电可靠性构成严重威胁。为有效识别配电网薄弱环节,提出一套适用于网架数字化建模与脆弱性评估的节点与线路脆弱性指标体系。对于节点脆弱性评估,除对传统指标(如节点度数...配电网中关键节点与主干线路的失效可能引发电网大规模故障,对供电可靠性构成严重威胁。为有效识别配电网薄弱环节,提出一套适用于网架数字化建模与脆弱性评估的节点与线路脆弱性指标体系。对于节点脆弱性评估,除对传统指标(如节点度数、节点介数、节点紧密中心度、节点注入功率及电压偏离度)进行优化外,进一步引入基于空间直接估计(spatial direct estimation,SDE)的结构脆弱性指标,以及考虑线路越限风险的抗扰动脆弱性指标;对于线路脆弱性评估,构建了线路度数、线路介数和线路SDE三类指标。基于上述指标体系,采用熵权法与直接赋权法分别确定节点与线路脆弱度权重,进而计算节点与线路的综合脆弱性评分。最后,以IEEE33节点系统和某中型城市中心城区实际配电网为例进行仿真验证,结果表明所提方法能有效辨识配电网节点与线路的薄弱环节,及时发现潜在运行隐患。展开更多
A Dark Network is a network that cannot be accessed through tradition means. Once uncovered, to any degree, dark network analysis can be accomplished using the SNA software. The output of SNA software includes many me...A Dark Network is a network that cannot be accessed through tradition means. Once uncovered, to any degree, dark network analysis can be accomplished using the SNA software. The output of SNA software includes many measures and metrics. For each of these measures and metric, the output in ORA additionally provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning best methods to disrupt or deceive a given dark network. In the Noordin Dark network, different nodes were identified as key nodes based upon the metric used. Our goal in this paper is to use methodologies to identify the key players or nodes in a Dark Network in a similar manner as we previously proposed in social networks. We apply two multi-attribute decision making methods, a hybrid AHP & TOPSIS and an average weighted ranks scheme, to analyze these outputs to find the most influential nodes as a function of the decision makers’ inputs. We compare these methods by illustration using the Noordin Dark Network with seventy-nine nodes. We discuss sensitivity analysis that is applied to the criteria weights in order to measure the change in the ranking of the nodes.展开更多
文摘Present work was designed to quantitatively evaluate the performance of diffusion-weighted magnetic resonance imaging（DWI） in the diagnosis of the presence of metastasis in lymph nodes（LNs）. Eligible studies were identified from systematical Pub Med and EMBASE searches. Data were extracted. Meta-analyses were performed to generate pooled sensitivity and specificity on the basis of per-node, per-lesion and per-patient, respectively. Fourteen publications（2458 LNs, 404 lesions and 334 patients） were eligible. Per-node basis demonstrated the pooled sensitivity and specificity was 0.82（P〈0.0001） and 0.90（P〈0.0001）, respectively. Per-lesion basis illustrated the pooled sensitivity and specificity was 0.73（P=0.0036） and 0.85（P〈0.0001）, respectively. Per-patient basis indicated the pooled sensitivity and specificity was 0.67（P=0.0909） and 0.86（P〈0.0001）, respectively. In conclusion, DWI has rather a negative predictive value for the diagnosis of LN metastasis presence. The difference of the mean apparent diffusion coefficients between benign and malignant LNs is not yet stable. Therefore, the DWI technique has to be further improved.
文摘Node of network has lots of information, such as topology, text and label information. Therefore, node classification is an open issue. Recently, one vector of node is directly connected at the end of another vector. However, this method actually obtains the performance by extending dimensions and considering that the text and structural information are one-to-one, which is obviously unreasonable. Regarding this issue, a method by weighting vectors is proposed in this paper. Three methods, negative logarithm, modulus and sigmoid function are used to weight-trained vectors, then recombine the weighted vectors and put them into the SVM classifier for evaluation output. By comparing three different weighting methods, the results showed that using negative logarithm weighting achieved better results than the other two using modulus and sigmoid function weighting, and was superior to directly concatenating vectors in the same dimension.
文摘Malignant melanoma is a malignancy of pigmentproducing cells(melanocytes) located predominantly in the skin. Nodal metastases are an adverse prognostic factor compromising long term patient survival. Therefore, accurate detection of regional nodal metastases is required for optimization of treatment. Computed tomography(CT) and magnetic resonance imaging(MRI) remain the primary imaging modalities for regional staging of malignant melanoma. However, both modalities rely on size-related and morphological criteria to differentiate between benign and malignant lymph nodes, decreasing the sensitivity for detection of small metastases. Surgery is the primary mode of therapy for localized cutaneous melanoma. Patients should be followed up for metastases after surgical removal. We report here a case of inguinal lymph node enlargement with a genital vesicular lesion with a history of surgery for malignant melanoma on her thigh two years ago. CT and diffusion weighted-MRI(DW-MRI) were applied for the lymph node identification. DW-MRI revealed malignant lymph nodes due to malignant melanoma metastases correlation with pathological findings.
文摘【目的】地球表层系统科学数据有向加权关联网络的关键节点识别对科学数据精准推荐与知识发现具有重要意义,但现有方法存在评估片面、特征利用不足及权重分配科学性欠缺等挑战。【方法】本文提出一种基于主客观融合权重的逼近理想解排序法(Technique for Order Preference by Similarity to an Ideal Solution, TOPSIS)的关键节点识别方法。首先,提出节点相似中心性指标,通过融合关联度与强度平衡局部拓扑与全局影响力;然后,构建整合网络拓扑、数据关联及节点相似性的多指标评价体系,全面刻画节点重要性;接着,提出双层权重优化策略,结合层次分析法(Analytic Hierarchy Process, AHP)和指标相关性定权法(Criteria Importance Through Intercriteria Correlation, CRITIC)方法,融合主客观权重,提升评估科学性;最后,结合TOPSIS评估方法进行节点重要性的综合评估。【结果】实验基于团队构建的不同规模的地表系统科学数据有向加权关联网络,结合加权易感-感染-恢复(SIR)模型进行实验验证,结果表明:与传统网络加权中心性以及基于主观或客观权重的TOPSIS等方法相比,本文方法在肯德尔相关系数值和TOP-K命中率方面表现更优,且在网络中展现强鲁棒性。【结论】该方法为地表系统科学数据网络分析提供了新方法,可支撑智能推荐、资源优化及系统脆弱性分析等实际应用,助力地球系统科学研究的深度发展。
文摘配电网中关键节点与主干线路的失效可能引发电网大规模故障,对供电可靠性构成严重威胁。为有效识别配电网薄弱环节,提出一套适用于网架数字化建模与脆弱性评估的节点与线路脆弱性指标体系。对于节点脆弱性评估,除对传统指标(如节点度数、节点介数、节点紧密中心度、节点注入功率及电压偏离度)进行优化外,进一步引入基于空间直接估计(spatial direct estimation,SDE)的结构脆弱性指标,以及考虑线路越限风险的抗扰动脆弱性指标;对于线路脆弱性评估,构建了线路度数、线路介数和线路SDE三类指标。基于上述指标体系,采用熵权法与直接赋权法分别确定节点与线路脆弱度权重,进而计算节点与线路的综合脆弱性评分。最后,以IEEE33节点系统和某中型城市中心城区实际配电网为例进行仿真验证,结果表明所提方法能有效辨识配电网节点与线路的薄弱环节,及时发现潜在运行隐患。
文摘A Dark Network is a network that cannot be accessed through tradition means. Once uncovered, to any degree, dark network analysis can be accomplished using the SNA software. The output of SNA software includes many measures and metrics. For each of these measures and metric, the output in ORA additionally provides the ability to obtain a rank ordering of the nodes in terms of these measures. We might use this information in decision making concerning best methods to disrupt or deceive a given dark network. In the Noordin Dark network, different nodes were identified as key nodes based upon the metric used. Our goal in this paper is to use methodologies to identify the key players or nodes in a Dark Network in a similar manner as we previously proposed in social networks. We apply two multi-attribute decision making methods, a hybrid AHP & TOPSIS and an average weighted ranks scheme, to analyze these outputs to find the most influential nodes as a function of the decision makers’ inputs. We compare these methods by illustration using the Noordin Dark Network with seventy-nine nodes. We discuss sensitivity analysis that is applied to the criteria weights in order to measure the change in the ranking of the nodes.
