Brilliance型16排螺旋CT的故障分析与维修

针对日常使用中遇到的Brilliance 16排螺旋CT高压系统、机架以及控制器局域网络(CAN)通讯等故障现象进行分析与维修,最终通过更换滤波电容、机架数据采集控制器(DMC)电源以及信号刷等配件得以排除故障。通过对故障准确判断以及合理运用厂家Service模式下的维修工具软件快速解决故障,保障了影像科检查工作的顺利进行,从而提高设备的稳定性。     

基于真实世界数据探讨中医药治疗糖尿病肾病用药规律的研究＊

目的 基于临床信息系统分析总结真实世界的数据，采用数据挖掘的方法探讨中医药治疗糖尿病肾病的用药规律。方法 收集2018年1月-2020年12月上海中医药大学附属曙光医院宝山分院健康信息系统确诊的糖尿病肾病的门诊或住院患者的诊疗信息，建立Excel数据库，采用Excel 2010软件统计高频药物的四气、五味、归经及功效；使用SPSS Modeler 18.0软件中的Apriori算法分析关联规则，采用web节点建构药对关联网状图；运用SPSS 25统计软件进行因子分析。结果 本研究最终纳入477例接受中药饮片治疗的DKD患者，在1203条方剂信息中，涉及中药462种；使用频数排名前5位的中药分别是黄芪、黄精、石斛、山茱萸、麦冬；使用频数前5类的中药类别分别是补气药、补阴药、清热燥湿药、活血调经药、息风止痉药；在30味高频药物中，苦、甘、辛药味最为常见；药性寒、温数量接近；归脾经、肝经、肺经、肾经居多；关联规则提示，药物组合中置信度最高的组合为地龙-当归-僵蚕，因子分析共得到5个有效因子，累积贡献率为47.33%。结论 中医药治疗DKD在补益气血阴阳的同时，兼顾对瘀血、湿邪和痰饮的治疗，结合证型，可考虑使用黄芪、黄精、石斛、山茱萸、麦冬、金蝉花等药物的使用，清热燥湿药物如黄连、黄芩、黄柏可适当加入，为使邪有去处，大黄、车前子或可增添疗效。     

Registries,Databases and Repositories for Developing Artificial Intelligence in Cancer Care

Modern artificial intelligence techniques have solved some previously intractable problems and produced impressive results in selected medical domains. One of their drawbacks is that they often need very large amounts of data. Pre-existing datasets in the form of national cancer registries, image/genetic depositories and clinical datasets already exist and have been used for research. In theory, the combination of healthcare Big Data with modern, data-hungry artificial intelligence techniques should offer significant opportunities for artificial intelligence development, but this has not yet happened. Here we discuss some of the structural reasons for this, barriers preventing artificial intelligence from making full use of existing datasets, and make suggestions as to enable progress. To do this, we use the framework of the 6Vs of Big Data and the FAIR criteria for data sharing and availability (Findability, Accessibility, Interoperability, and Reuse). We share our experience in navigating these barriers through The Brain Tumour Data Accelerator, a Brain Tumour Charity-supported initiative to integrate fragmented patient data into an enriched dataset. We conclude with some comments as to the limits of such approaches.     

High Order Finite Difference Hermite WENO Fixed-Point Fast Sweeping Method for Static Hamilton-Jacobi Equations

In this paper, we combine the nonlinear HWENO reconstruction in [43] and the fixed-point iteration with Gauss-Seidel fast sweeping strategy, to solve the static Hamilton-Jacobi equations in a novel HWENO framework recently developed in [22]. The proposed HWENO frameworks enjoys several advantages. First, compared with the traditional HWENO framework, the proposed methods do not need to introduce additional auxiliary equations to update the derivatives of the unknown function $\phi$. They are now computed from the current value of $\phi$ and the previous spatial derivatives of $\phi$. This approach saves the computational storage and CPU time, which greatly improves the computational efficiency of the traditional HWENO scheme. In addition, compared with the traditional WENO method, reconstruction stencil of the HWENO methods becomes more compact, their boundary treatment is simpler, and the numerical errors are smaller on the same mesh. Second, the fixed-point fast sweeping method is used to update the numerical approximation. It is an explicit method and does not involve the inverse operation of nonlinear Hamiltonian, therefore any Hamilton-Jacobi equations with complex Hamiltonian can be solved easily. It also resolves some known issues, including that the iterative number is very sensitive to the parameter $ε$ used in the nonlinear weights, as observed in previous studies. Finally, to further reduce the computational cost, a hybrid strategy is also presented. Extensive numerical experiments are performed on two-dimensional problems, which demonstrate the good performance of the proposed fixed-point fast sweeping HWENO methods.     

Custom made cutting guides and osteosynthesis plates versus CAD/CAM occlusal splints in positioning and fixation of the maxilla in orthognathic surgery: A prospective randomized study

The aim of this study is to compare the accuracy of maxilla positioning in orthognathic surgery with the use of custom-made devices (cutting guides and patient-fitted osteosynthesis plates) comparing to CAD/CAM splints.A prospective randomized study was performed. Patients with dentofacial deformities undergoing orthognathic surgery were compared, using customized guides (experimental group) vs. CAD/CAM surgical splints (control group) for the repositioning of the upper maxilla. Preoperative and postoperative CT scans were used to compare positioning and fixation of the maxilla in the three planes of space.A total of 30 patients were included in the study (15 patients in each study group). The mean error obtained with customized guides was 0.8 mm (range 0.1–1.9) in the anterior-posterior axis, 0.4 mm (range 0–1.4) in the vertical axis and 0.2 mm (range 0–1.1) in the horizontal axis. There were statistically significant differences in the anterior-posterior and vertical axes in favour of the customized implants, whereas there were no differences in the horizontal plane. Furthermore, there was a mean reduction of the operative time of 36.5 min in the experimental group.Within the limitations of the study it seems that patient specific surgical guides should be preferred when accuracy of repositioning of the maxilla and saving operative time are the priority.     

Preoperative comprehensive malignancy risk estimation for thyroid nodules: Development and verification of a network-based prediction model

BackgroundIn order to avoid excessive treatment of thyroid nodules in the clinic, it is necessary to find a simple and practical analysis method to comprehensively and accurately reflect benign or malignant thyroid nodules. This study aimed to construct and validate a comprehensive and reliable network-based predictive model using a variety of imaging and laboratory criteria for thyroid nodules to stratify the risk of malignancy prior to surgery.MethodsWe retrospectively analyzed data from patients who underwent surgical treatment for thyroid nodules at the Thyroid and Breast Diagnosis and Treatment Center of Weifang Hospital of Traditional Chinese Medicine between January 2018 and December 2020. Binary logical regression analysis was performed to predict whether nodules were malignant or benign. The developmental dataset included 457 patients (January 2018–December 2020). The validation set included separate data points (n = 225, January 2018–December 2020).ResultsIn this study, criteria that showed significant predictive value for malignant nodules included TI-RADS: 4b (p = 0.065); Bethesda IV, Bethesda V, Bethesda VI (P < 0.0001); BRAF^V600E mutation (P < 0.0001); Calcitonin>5 pg/ml (p = 0.0037); and FNA-Tg>30 ng/ml (p = 0.0003). A 10-grade risk scoring system was developed. The risk of malignancy risk ranged from 2.06% to 100% and was positively associated with increasing risk grade. The areas under the receiver-operating characteristic curve of the development and validation sets were 0.972 and 0.946, respectively.ConclusionA simple, comprehensive and reliable web-based predictive model was designed using a variety of imaging and laboratory criteria to stratify thyroid nodules by probability of malignancy.     

The effectiveness of humanoid diagram teaching strategy on care capacity and retention in novice nurses

AimTo examine the effectiveness of a Humanoid Diagram Teaching Strategy (HDTS) on care capabilities and retention of novice nurses.BackgroundGuiding novice nurses in clinical practice is a matter of concern and the use of diagrams in assisting the learning process and to promote learning efficiency has been acknowledged.DesignThis is a quasi-experimental study with asynchronous repeated measurements for the experimental and control groups.MethodsThe study was conducted in a medical centre in southern Taiwan with 24 novice nurses. The intervention, Humanoid Diagrams Teaching Strategy, contained three parts: the head and neck; trunk; and limbs. The HDTS was applied three time weekly. Each session lasted approximately 30 min and the training lasted 4 weeks. The effectiveness of HDTS was measured using Mini-CEX, CbD and retention rates in the 3rd and 6th months of novice nurses’ experience.ResultsAfter the HDTS, although increases in mini-CEX and CbD scores in the experimental group were greater than the control group, these differences were not statistically significant after considering the time interaction. But the 3rd month and 6th month novice nurses’ retention rates were statistically significantly different by comparing the differences under the time interaction effects in both groups.ConclusionsThe Humanoid Diagram Teaching Strategy is an effective tool for preceptors to use in assisting novice nurses in learning, improving their nursing care knowledge and technical skills and to increase their retention rate.     

Contributions of the NICHD neonatal research network's generic database to documenting and advancing the outcomes of extremely preterm infants

The Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network (NRN) maintains a database of extremely preterm infants known as the Generic Database (GDB). Begun in 1987, this database now includes more than 91,000 infants, most of whom are extremely preterm (<29 weeks gestation). The GDB has been the backbone of the NRN, providing high quality, prospectively collected data to study the changing epidemiology of extreme prematurity and its outcomes over time. In addition, GDB data have been used to generate hypotheses for prospective studies and to develop new clinical trials by providing information about the numbers and characteristics of available subjects and the expected event rates for conditions and complications to be studied. Since its inception, the GDB has been the basis of more than 200 publications in peer-reviewed journals, many of which have had a significant impact on the field of neonatology.     

红外光谱数据融合对栽培滇重楼产地鉴别*

目的 多样的环境因素使得不同产地栽培滇重楼的化学成分也丰富多样，不同居群栽培滇重楼的甾体皂苷类成分具有很大的差异，多源数据融合分析能更全面的表征药材化学信息，建立一个高效而准确的产地鉴别模型，为其资源合理开发利用提供依据。方法 以来自云南和四川的8个产地（保山、楚雄、大理、红河、丽江、成都、文山、玉溪）共366份栽培滇重楼根茎为实验材料，采集其傅里叶变换近红外光谱（FT-NIR）和衰减全反射-傅里叶变换中红外光谱（ATR-FTMIR）数据。采用Kennard-Stone算法将不同产地的样品分为2/3的训练集和1/3的预测集，基于4种特征变量提取方法（CARS、VIP、SPA、SO-Covsel）结合2种数据融合策略（低级数据融合和中级数据融合），建立偏最小二乘产地判别分析模型。根据模型参数交叉验证均方根误差（RMSECV）和预测均方根误差（RMSEP）评估模型的稳定性，模型训练集和预测集准确率（ACC）评估模型分类性能。结果 近红外光谱和中红外光谱均能反应不同产地栽培滇重楼的化学成分差异，在中级数据融合中，基于VIP和SPA提取的特征变量建立的模型正确率均大于94%。相较于中级数据融合，低级数据融合模型得到了最为满意的结果，其预测集分类正确率达到100%。结论 根据近红外和中红外数据建立的低级数据融合PLS-DA模型，能够用于栽培滇重楼的产地鉴别分析。