基于“互联网+”的《临床检验仪器学》虚拟仿真教学实践

《临床检验仪器学》是一门实践性课程,为改变目前教学中实验场地局限、大型自动化检测仪器缺乏等限制,提出《临床检验仪器学》虚拟仿真教学探索思路。本文基于医学检验应用型人才培养目标,形成检验仪器学单个仪器和综合项目训练的虚拟仿真教学设计与管理举措;构建教学效果评价与质量监控的方法,显著提高学生的自主学习能力和综合实践能力;借助互联网共享优势促进医学检验实验教学的内涵建设。     

An intelligent system for diagnosis of the heart valve diseases with wavelet packet neural networks

In this paper, an intelligent system is presented for interpretation of the Doppler signals of the heart valve diseases based on the pattern recognition. This paper especially deals with combination of the feature extraction and classification from measured Doppler signal waveforms at the heart valve using the Doppler Ultrasound. Because of this, a wavelet packet neural network model developed by us is used. The model consists of two layers: wavelet and multi-layer perceptron. The wavelet layer is used for adaptive feature extraction in the time-frequency domain and is composed of wavelet packet decomposition and wavelet packet entropy. The multi-layer perceptron used for classification is a feed-forward neural network. The performance of the developed system has been evaluated in 215 samples. The test results showed that this system was effective in detecting Doppler heart sounds. The correct classification rate was about 94% for abnormal and normal subjects.     

血糖感应型胰岛素给药智能载体的研究进展

胰岛素控制释放高分子载体系统一直是国内外科技工作者的研究热点 ,迄今已经研究报道了多种具有不同工作原理的血糖感应型胰岛素给药智能载体。本文基于国内外大量研究文献 ,综述了血糖感应型胰岛素控制释放智能化高分子载体的研究进展。     

心电信号预处理与心电信号分析

本文介绍了在一种便携式心电监护仪器中是如何对心电数据进行预处理和智能分析的．为了适应便携式仪器的特征，我们在心电信号预处理中采用了FFT滤波和滑动平均滤波的方法去除各种干扰并使图像得以平滑，同时采用了差分阈值法提取特征点，考虑到监护仪器的实用性，在心电信号分析阶段，我们采用了分析特征间期异常情况的方法来替代对病症的智能诊断功能。     

基于智能化平台的医院配电系统安全探讨

结合实例,对医院建设配电安全平台的需求进行分析,阐述了配电安全平台的开发思路及系统功能,总结出应用配电智能化系统的成效。     

慢性创伤伤口智能问诊系统的研制

目的:研发一种在收集微信端即可对慢性创伤伤口进行智能问诊的系统软件,以规范化慢性创伤伤口采集的规范化及合理化。方法:采用目前普及度最为广泛的微信端口收集数据,搭建云平台存储数据,将慢性创伤伤口按照规范化方式收集数据。结果:问诊系统规范了慢性创伤伤口治疗,使案例收集更为模式化,加强了医生和护士对创伤伤口处理的方式方法的选择准确性。结论:慢性创伤伤口智能问诊系统可对伤口进行规范化评估,根据数据分析明确治疗方案的选择;详细化的对患者建立电子病例档案,便于后期资料查询、病历统计、后期随访和管理;利于临床医疗、教学和科学研究。     

城市一体化输血管理智慧云平台构建

结合智慧城市建设规划,依托射频识别技术,建立血液物联及冷链监管系统,整合并优化血站、医院输血管理信息系统,建立城市一体化输血管理智慧云平台,实现了血液从“血管到血管”全流程的信息追溯,为城市智慧应急用血提供了决策依据。     

脊柱手术机器人在脊柱外科手术中的应用进展

过去十年间,智能医疗技术已经成为研究的热点方向,并衍生出图像辅助AI和肿瘤诊断辅助系统等一系列技术.在外科领域,外科机器人是最有吸引力的智能技术之一.经过近十年的发展,机器人在脊柱外科手术中显露出巨大优势,已有大量关于准确性和辐射量的研究报道.但是,文献查阅过程中亦暴露出机器人的一些不足,促使我们对脊柱机器人的综合评价进行了回顾.此综述总结了已发表文章中提到的结果和我们已总结而未发表的结论,希望这些总结有助于研究人员将来对机器人进行针对性的改进,并拓宽脊柱手术机器人的未来方向.脊柱手术机器人技术被认为在未来应用中前景光明,但是与其他现有的应用技术相比,亟须解决应用范围窄、应用深度浅和优势不突出的缺点.     

以患者为中心的智慧医疗应用模式研究与实践

阐述医院信息化与智慧医疗的关系，对国内外医院信息化与智慧医疗发展状况进行分析。结合武汉市中心医院智慧医疗创新应用的实践经验，从关键技术、应用效果等方面提出一种以患者为中心的智慧医疗应用模式。     

Deep learning for intelligent diagnosis in thyroid scintigraphy

ObjectiveTo construct deep learning (DL) models to improve the accuracy and efficiency of thyroid disease diagnosis by thyroid scintigraphy.MethodsWe constructed DL models with AlexNet, VGGNet, and ResNet. The models were trained separately with transfer learning. We measured each model’s performance with six indicators: recall, precision, negative predictive value (NPV), specificity, accuracy, and F1-score. We also compared the diagnostic performances of first- and third-year nuclear medicine (NM) residents with assistance from the best-performing DL-based model. The Kappa coefficient and average classification time of each model were compared with those of two NM residents.ResultsThe recall, precision, NPV, specificity, accuracy, and F1-score of the three models ranged from 73.33% to 97.00%. The Kappa coefficient of all three models was >0.710. All models performed better than the first-year NM resident but not as well as the third-year NM resident in terms of diagnostic ability. However, the ResNet model provided “diagnostic assistance” to the NM residents. The models provided results at speeds 400 to 600 times faster than the NM residents.ConclusionDL-based models perform well in diagnostic assessment by thyroid scintigraphy. These models may serve as tools for NM residents in the diagnosis of Graves’ disease and subacute thyroiditis.