基于基因组合模式挖掘的辅助诊断专家系统

在医疗领域中,基因芯片技术等高效核酸分析手段不断发展,使得临床诊断与医学研究中能够利用这一技术获取大量与肿瘤生成相关的基因信息。同时,近年来随着机器学习理论与技术的不断发展与应用,在各领域内出现了大量基于人工智能技术的专家系统。针对基因芯片信息的特点,描述了一种肿瘤辅助诊断专家系统的设计思路与实现方案;讨论了在专家系统实现过程中所采用的关键数据挖掘技术;重点叙述了系统的结构框架、工作机制与辅助诊断原理。在实验中,展示了临床获得的医疗数据在所论述系统中的测试结果。实验结果表明所论述的系统实现方案能够在一定程度上满足辅助诊断的需求。     

ENHANCEMENT OF THE CAPABILITIES OF AN NMR IMAGING MACHINE USING EXPERT SYSTEMS

ABSTRACT

Practical effectiveness of NMR imaging in diagnostic medicine can be considerably upgraded by incorporating into the machine high-level intelligent software support. Partly because NMR imaging is a relatively new technology, knowledge acquisition is essentially related to incoming new experience. Therefore an expert system approach to NMR medical applications should rely on rule induction techniques based on a series of example expert decisions. The complete project consists of three main components: (1) a protocol expert system, (2) a diagnosis expert system, and (3) a vision system. Expert system prototypes regarding part 1 and 2 of this study were built indicating preliminary interesting results. These results justify our attempts aimed at the enhancement of NMR capabilities as a diagnostic tool and consequent commercial benefits.     

新型冠状病毒肺炎(COVID-19)医学影像AI诊断研究进展

2020年3月,世界卫生组织（World Health Organization,WHO）宣布新型冠状病毒肺炎（corona virus disease 2019,COVID-19）为世界大流行病,疫情的爆发给世界各地医疗系统带来巨大压力。现有的COVID-19诊断标准是核酸检测阳性,然而核酸检测假阴性率高达17%~25.5%,为避免漏诊,需要采用基于影像学的AI诊断方法筛查大量疑似病例,扼制疾病传播。本综述将回顾疫情爆发数月以来,基于医学影像的新冠肺炎AI辅助诊断的研究成果。首先介绍CT（computed tomography）和X光片的优缺点,以及COVID-19的放射学特征,然后对数据准备、图像分割和分类识别等AI诊断的关键步骤分别进行阐述,最后介绍COVID-19的跟踪和预后（预先对疾病后续发展过程及结果的判断和估计）。本文还整理了部分公开的COVID-19相关数据集,并对数据标注不足的问题提供了弱监督学习和迁移学习等解决方案。实验验证,AI系统诊断COVID-19的敏感性达到97.4%,特异性达到92.2%,优于放射科医生的诊断结果。其中表现尤为突出的是基于语义分割网络检测COVID-19感染区域,由此可以定量分析感染率。AI系统可以辅助医生诊断和治疗COVID-19,提高放射科医生阅读X光片和CT的效率。     

基于单片机的制氧控制系统

通过本控制系统的研究,实现PSA系列医用制氧设备的集成化和智能化控制,为我军提供高效的智能型医用制氧设备。本控制系统是以PSA医用制氧设备为控制对象,根据分子筛变压吸附(PSA)制氧技术及其总体方案来确立的,并通过LPC935系列单片机来实现。试制结果表明,该控制方案是有效的。     

Digital teaching files in diagnostic imaging

An architecture for digital teaching of radiology targets the next generation of network based education in diagnostic imaging. We developed applications of this system in UCSF hospitals (San Francisco, USA). The networked digital teaching file for medical imaging presented here builds on the availability of existing clinical information infrastructure in hospitals, such as PACS and RIS, and the recent advances in open systems Internet technology. Such a digital teaching file possesses enormous potential to change the practice and landscape of medical imaging education. Countries throughout the world share the goal of improving health care productivity and quality. They must invest not only in clinical services, but also in effective training of a new generation of imaging specialists. A networked digital teaching file provides a cost effective tool for attaining this goal     

基于微流控技术的体外多参数快速诊断POCT系统的设计

针对传统的体外快速诊断系统(POCT)精度低、参数单一等问题,设计了一种基于微纳传感结合微流控技术的多参数体外快速诊断POCT系统.本文研究了传感器与微流控芯片的制备工艺、传感器微弱信号的采集与提取、多通道参考电极的多维度抗干扰校正算法以及多参数POCT系统的优化设计,保证了POCT系统具有检测精度高、抗干扰性能好、多参数集成等特点.通过系统测试和临床实际样本的基本性能测试,实验结果表明,本文提出的多参数体外诊断快速检测POCT系统能够综合检测血糖、血酮等多项指标,具备快速,精确,多参数测量的特点,将为基层医疗机构的生化指标检测提供一种新型实用的技术和仪器.     

基于MNSS的医学影像虚拟仿真实训平台设计

医学影像诊断学是一门实践性较强的学科,学生既要掌握理论知识,又要通过接触大量的临床影像病例来提高阅片能力,理论与实践相辅相成达到较好的教学效果。然而学生临床见习时间比较少,见习时学生比较多,实践教学效果不够理想,针对这一问题开发一套具有自主影像诊断学习功能的医学影像虚拟仿真实训平台,该平台采用C/S架构,PACS影像存储服务器使用Linux+FTP+Mysql技术架构。利用F5_BIG_IP 负载均衡技术和MNSS(Medical Network System Simulator)仿真软件,构建了一个分布式的医学影像虚拟仿真平台。经过学生的课堂实验测试,系统运行稳定,能够满足学生的诊断学习需求,具有较好的推广价值。     

可视化技术在医院临床应用及展望

医学三维可视化技术的研究发展,促进了临床医学不断进步.可视化技术已渗透应用到医院临床,给临床诊断治疗带来突破性进展,提高了整体医疗诊断治疗水平,提升了临床医学教学科研能力,开拓了新的临床治疗领域.可视化技术在医院临床有广泛的应用空间和前景.浅谈了医学可视化技术在医院临床诊断治疗、计算机辅助手术、远程医疗、教学科研等应用及展望.     

Interactive visual tools as triggers of collaborative reasoning in entry-level pathology

The growing importance of medical imaging in everyday diagnostic practices poses challenges for medical education. While the emergence of novel imaging technologies offers new opportunities, many pedagogical questions remain. In the present study, we explore the use of a new tool, a virtual microscope, for the instruction and the collaborative learning of pathology. Fifteen pairs of medical students were asked to solve diagnostic tasks in a virtual microscopy learning environment. The students?? collaborative efforts were analysed on the basis of approximately 20 hours of video recordings. Our analyses show how students use the technology as a mediating tool to organize, manipulate and construct a shared visual field, and later, shared understanding of the problem and solutions. Organization of the visual field is done through multimodal referential practices: gestures, three dimensional manipulation of the image and paced inspection of the specimen. Furthermore, we analyse and describe how the aforementioned practices coincide with students?? medical reasoning in this particular learning context. The analysis of medical students?? diagnostic work illustrates the collaborative potential of the virtual microscopy environment and how such interactive tools render the traditional distinction between collaborating around or through computers irrelevant, as even face to face collaboration becomes enacted through technology. Finally, we argue that as technologies develop, understanding the technical side of image production, or any representation, becomes an integral part of the interpretative process. How this knowledge is communicated to the students may play a substantive role in how students learn to interpret medical images.     

Getting Chipped: To Ban or Not to Ban

Human Radio Frequency Identification (RFID) implants are currently being marketed as a way to limit access to secure areas or as anti-kidnapping devices, as well as means to track and quickly identify in emergency situations individuals with serious medical conditions or mental disabilities or to serve as cashless payment devices with a wave of the hand. While in certain instances, such as in some medical applications, this technology can have positive and benign effects there are also serious privacy implications. Although at present, technological and financial challenges prevent the wide take-up of these highly controversial devices, privacy advocates fear the technology might be abused by governments and big corporations and used to constantly locate and profile people. A detailed critique of the complex privacy, security, ethical and health implications in the light of this emerging technology is still lacking and this article attempts to contribute to this process.     

The TERESA project: from space research to ground tele-echography

Ultrasound examinations represent one of the major diagnostic modalities of future healthcare. They are currently used to support medical space research but require a high skilled operator for both probe positioning on the patient's skin and image interpretation. TERESA is a tele-echography project that proposes a solution to bring astronauts and remotely located patients on ground quality ultrasound examinations despite the lack of a specialist at the location of the wanted medical act.     

用于远程汽车故障诊断系统的安全访问控制

根据对远程汽车故障诊断系统工作原理与通信访问特点的分析,设计了系统安全访问控制方案,包括远程诊断仪与系统诊断中心的GPRS安全接入,GPRS与Intranet间的安全访问控制,以及基于SSL VPN技术的身份认证与用户授权。最后,基于设计方案提出了系统安全访问控制的体系结构和实现过程,并通过实验证明了该方案的可行性,验证了该方案具有良好的安全访问控制效果。     

Image processing and machine learning for fully automated probabilistic evaluation of medical images

The paper presents results of our long-term study on using image processing and data mining methods in a medical imaging. Since evaluation of modern medical images is becoming increasingly complex, advanced analytical and decision support tools are involved in integration of partial diagnostic results. Such partial results, frequently obtained from tests with substantial imperfections, are integrated into ultimate diagnostic conclusion about the probability of disease for a given patient. We study various topics such as improving the predictive power of clinical tests by utilizing pre-test and post-test probabilities, texture representation, multi-resolution feature extraction, feature construction and data mining algorithms that significantly outperform medical practice. Our long-term study reveals three significant milestones. The first improvement was achieved by significantly increasing post-test diagnostic probabilities with respect to expert physicians. The second, even more significant improvement utilizes multi-resolution image parametrization. Machine learning methods in conjunction with the feature subset selection on these parameters significantly improve diagnostic performance. However, further feature construction with the principle component analysis on these features elevates results to an even higher accuracy level that represents the third milestone. With the proposed approach clinical results are significantly improved throughout the study. The most significant result of our study is improvement in the diagnostic power of the whole diagnostic process. Our compound approach aids, but does not replace, the physician's judgment and may assist in decisions on cost effectiveness of tests.     

一种用于表面重建的外边界轮廓线提取算法

医学图像处理中边界轮廓线的提取是科学计算可视化技术中的一个研究热点,足计算机图形学和图像处理技术在生物医学工程中的重要应用.在医学图像的三维重建、模式识别等的应用中,常常需要保留感兴趣的物体区域,从而必须用外边界作为轮廓线.在分析Log算了作用原理的基础上,提出片实现了一种新的按光栅顺序扫描取点然后进行边界跟踪的轮廓线提取算法,最后按照最短对角线法进行轮廓连接.实验证明,算法可以有效地消除噪声,获得更加精确的象素级边界轮廓,重建效果较为满意.     

Organizing the clinical data in the medical record.

We have developed a method of collecting and arranging clinical data that makes the medical record more useful in patient care and research. The design is based on two principles: that detailed clinical findings should be recorded independently of any diagnostic interpretation, and that time should be integrated as a dimension of the medical record. Analysis of the principal components of the medical record as we have organized it allows identification of clinical entities on the basis of synchronous or sequential features and facilitates precise tracking of symptoms, evaluation of therapeutic effects, comparison of treatments, identification of patients at risk of recurrence, transmission of observations from physician to physician, and analysis and reinterpretation of the observations recorded.     

医用含铜抗菌金属——从研究走上应用

我国在医用抗菌金属的研究方面走在国际前列,其应用有望有效地降低与医疗器械或植入物相关的细菌感染发生率,具有重要的临床价值。该文简要介绍了我国在医用含铜抗菌金属方面的创新研究及其在医学领域中的初步应用,并对未来面临的机遇与挑战进行了分析。     

OpenClinical.net: A platform for creating and sharing knowledge and promoting best practice in healthcare

It is well known that medical knowledge is growing so rapidly that it is difficult or impossible for healthcare professionals to keep up. More and more techniques for diagnosing and treating diseases are becoming available, yet new research findings and clinical practices are slow to spread. Information technology and the internet are providing important new ways of disseminating knowledge in healthcare as in many other domains. Knowledge engineering techniques for supporting decision-making and process management are also becoming available, and can be used to support busy clinicians, helping to ensure that their decisions are consistent with current knowledge and clinical procedures are carried out in a timely, efficient and safe way. The OpenClinical.net project is building on these techniques to demonstrate a new paradigm for disseminating knowledge and promoting best practice. The key idea is that much professional expertise can be modelled as computer-interpretable knowledge and used to assist decision-making, workflow management, communication and coordination of care and many other professional tasks. The central goal of OpenClinical.net is to demonstrate how this might be done at scale, through a form of “crowd sourcing”, in order to create and maintain a sharable knowledge base that is available in an open access and open source repository. This paper provides an overview of the project and a summary of progress to date.     

A knowledge centric methodology for dental implant technology assessment using ontology based patent analysis and clinical meta-analysis

The medical equipment industry has been one of the fastest growing sectors of the decade with predicted global sales reaching US$ 430 billion in 2017 [22]. During the period from 1995 to 2008, the patent applications in medical technology increased rapidly worldwide (World Intellectual Property Organization, 2012). Patent analysis, although useful in forecasting technology development trends, has posed a challenging analysis task since the volume and diversity of new patent applications has surpassed the ability of regular firms and research teams to process and identify relevant information. Further, medical related technologies rely on clinical trials to validate and gain regulatory approval for patient treatment even though patents, protecting the intellectual property rights of inventors, have been granted. This research focuses on developing a knowledge centric methodology and system to analyze and assess viable medical technology innovations and trends considering both patents and clinical reports. Specifically, the design innovations of dental implant connections are used as a case study. A novel and generic methodology combining ontology based patent analysis and clinical meta-analysis is developed to analyze and identify the most effective patented techniques in the dental implant field. The research establishes and verifies a computer supported analytical approach and system for the strategic prediction of medical technology development trends.     

基于CRF模型的临床医嘱信息实体识别方法应用研究

将命名实体识别技术运用于临床业务系统中,实现对临床医嘱的实体识别,提高临床医疗的工作效率。以上海市胸科医院为研究背景,提出嵌入于临床业务信息系统的临床医嘱实体识别方法。基于历年医嘱数据建立专项语料词库,运用CRF模型进行实时实体识别。随着识别系统上线使用,共处理了8362条医嘱,实验结果表明其准确率较好,在信息支撑度方面提升了医护人员的满意度。医嘱实体识别技术能够有效提高执行效率和医疗质量,也为医疗领域的知识挖掘工作提供了参考依据。     

On the applicability of diagnostic criteria for the diagnosis of rheumatoid arthritis in an expert system

-2/ is a medical expert system developed to assist in the differential diagnosis of rheumatic diseases. Based on fuzzy set theory and fuzzy logic, it supports the formalization of vague and uncertain medical information (i.e., medical entities and relationships between them) and draws justifiable conclusions from these imprecise data. Given a patient's finding patter, -2 provides confirmed and excluded diagnoses, diagnostic hypotheses, and suggestions for further examinations. The knowledge base of -2 has been designed to contain simple finding/disease relationships as well as diagnostic rules of high complexity to confirm or hypothesize disease. We shall present results obtained with 300 clinical cases from a hospital for rheumatic diseases. Different rules for the diagnosis of rheumatoid arthritis based upon classification criteria issued by the American Rheumatism Association were tested against each other. That diagnostic rule which had shown the best results was then further improved by a rheumatology expert, which finally yielded a sensitivity of 83.3% and a specificity of 95.3%.