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
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
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
针对基本的快速搜索随机树(rapidly-exploring random tree,RRT)算法用于路径规划时存在的树扩展无导向性、密集障碍物区域规划效率低、局部区域节点聚集等问题,提出一种新的RRT改进算法。该算法采用增强的目标偏向策略,并引入可变的权...针对基本的快速搜索随机树(rapidly-exploring random tree,RRT)算法用于路径规划时存在的树扩展无导向性、密集障碍物区域规划效率低、局部区域节点聚集等问题,提出一种新的RRT改进算法。该算法采用增强的目标偏向策略,并引入可变的权值系数,提高随机树扩展的导向性和灵活性;同时采用局部节点过滤机制,过滤局部区域内聚集的节点;最后,使用节点直连策略对初始路径进行优化处理。仿真实验的结果表明,改进的RRT算法规划路径的速度更快且生成的路径质量更高,充分证明了改进算法的有效可行性。展开更多
目的探讨基于多参数MRI的瘤内和瘤周影像组学特征术前预测临床淋巴结阴性乳腺癌淋巴血管浸润(LVI)的价值。资料与方法回顾性分析2017年1月—2021年5月河南省人民医院术后病理证实的280例乳腺癌临床病理及乳腺MRI资料,其中LVI阳性100例,...目的探讨基于多参数MRI的瘤内和瘤周影像组学特征术前预测临床淋巴结阴性乳腺癌淋巴血管浸润(LVI)的价值。资料与方法回顾性分析2017年1月—2021年5月河南省人民医院术后病理证实的280例乳腺癌临床病理及乳腺MRI资料,其中LVI阳性100例,阴性180例;并将其随机分为训练集和测试集。经Z分数归一化、Select K Best和最小绝对收缩与选择算子回归筛选特征,采用随机森林算法分别构建瘤内、瘤周及瘤内-瘤周影像组学模型预测LVI状态。以受试者工作特征曲线下面积(AUC)、校准曲线和决策曲线分析评估模型性能和临床应用价值。结果Ki-67高表达(≥20%)、腋窝淋巴结转移和扩散加权成像(DWI)边缘征阳性在LVI阳性组中比例较高(χ^(2)=5.959、18.316、20.554,P<0.05)。在测试集,动态对比增强(DCE)瘤内模型和DCE瘤内-瘤周模型预测LVI状态的AUC高于DWI序列,而DWI瘤周模型的AUC高于DCE序列。DWI联合DCE序列的瘤内-瘤周模型在训练集和测试集的AUC分别为0.836和0.818,其预测LVI状态的效能高于单序列瘤内-瘤周模型。决策曲线分析显示,DWI联合DCE序列的瘤内-瘤周模型在合理阈值范围内具有更高的临床净效益。结论基于多参数MRI瘤内及瘤周影像组学模型可有效预测临床淋巴结阴性乳腺癌LVI状态,为术前制订个体化治疗决策提供参考。展开更多
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.
文摘针对基本的快速搜索随机树(rapidly-exploring random tree,RRT)算法用于路径规划时存在的树扩展无导向性、密集障碍物区域规划效率低、局部区域节点聚集等问题,提出一种新的RRT改进算法。该算法采用增强的目标偏向策略,并引入可变的权值系数,提高随机树扩展的导向性和灵活性;同时采用局部节点过滤机制,过滤局部区域内聚集的节点;最后,使用节点直连策略对初始路径进行优化处理。仿真实验的结果表明,改进的RRT算法规划路径的速度更快且生成的路径质量更高,充分证明了改进算法的有效可行性。
文摘目的探讨基于多参数MRI的瘤内和瘤周影像组学特征术前预测临床淋巴结阴性乳腺癌淋巴血管浸润(LVI)的价值。资料与方法回顾性分析2017年1月—2021年5月河南省人民医院术后病理证实的280例乳腺癌临床病理及乳腺MRI资料,其中LVI阳性100例,阴性180例;并将其随机分为训练集和测试集。经Z分数归一化、Select K Best和最小绝对收缩与选择算子回归筛选特征,采用随机森林算法分别构建瘤内、瘤周及瘤内-瘤周影像组学模型预测LVI状态。以受试者工作特征曲线下面积(AUC)、校准曲线和决策曲线分析评估模型性能和临床应用价值。结果Ki-67高表达(≥20%)、腋窝淋巴结转移和扩散加权成像(DWI)边缘征阳性在LVI阳性组中比例较高(χ^(2)=5.959、18.316、20.554,P<0.05)。在测试集,动态对比增强(DCE)瘤内模型和DCE瘤内-瘤周模型预测LVI状态的AUC高于DWI序列,而DWI瘤周模型的AUC高于DCE序列。DWI联合DCE序列的瘤内-瘤周模型在训练集和测试集的AUC分别为0.836和0.818,其预测LVI状态的效能高于单序列瘤内-瘤周模型。决策曲线分析显示,DWI联合DCE序列的瘤内-瘤周模型在合理阈值范围内具有更高的临床净效益。结论基于多参数MRI瘤内及瘤周影像组学模型可有效预测临床淋巴结阴性乳腺癌LVI状态,为术前制订个体化治疗决策提供参考。
