Cascaded PFLANN Model for Intelligent Health Informatics in Detection of Respiratory Diseases from Speech Using Bio-inspired Computation

Due to the recent developments in communications technology,cognitive computations have been used in smart healthcare techniques that can combine massive medical data,artificial intelligence,federated learning,bio-inspired computation,and the Internet of Medical Things.It has helped in knowledge sharing and scaling ability between patients,doctors,and clinics for effective treatment of patients.Speech-based respiratory disease detection and monitoring are crucial in this direction and have shown several promising results.Since the subject’s speech can be remotely recorded and submitted for further examination,it offers a quick,economical,dependable,and noninvasive prospective alternative detection approach.However,the two main requirements of this are higher accuracy and lower computational complexity and,in many cases,these two requirements do not correlate with each other.This problem has been taken up in this paper to develop a low computational complexity-based neural network with higher accuracy.A cascaded perceptual functional link artificial neural network(PFLANN)is used to capture the nonlinearity in the data for better classification performance with low computational complexity.The proposed model is being tested for multiple respiratory diseases,and the analysis of various performance matrices demonstrates the superior performance of the proposed model both in terms of accuracy and complexity.

Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic outbreaks.This review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their performance.Since,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by SM.This paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic outbreaks.DL has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation results.In recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM analysis.This paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM analysis.Finally,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

Medical Informatics:概念与历史

历数Medical Informatics的定义,总结出这些定义的共有特点;回顾Medical Informatics在美国的历史,并且介绍它在中国的发展状况。

Managing Health Treatment by Optimizing Complex Lab-Developed Test Configurations: A Health Informatics Perspective

A complex Laboratory Developed Test(LDT)is a clinical test developed within a single laboratory.It is typically configured from many fea-ture constraints from clinical repositories,which are part of the existing Lab-oratory Information Management System(LIMS).Although these clinical repositories are automated,support for managing patient information with test results of an LDT is also integrated within the existing LIMS.Still,the support to configure LDTs design needs to be made available even in standard LIMS packages.The manual configuration of LDTs is a complex process and can generate configuration inconsistencies because many constraints between features can remain unsatisfied.It is a risky process and can lead patients to undergo unnecessary treatments.We proposed an optimized solution(opt-LDT)based on Genetic Algorithms to automate the configuration and resolve the inconsistencies in LDTs.Opt-LDT encodes LDT configuration as an optimization problem and generates a consistent configuration that satisfies the constraints of the features.We tested and validated opt-LDT for a local secondary care hospital in a real healthcare environment.Our results,averaged over ten runs,show that opt-LDT resolves 90%of inconsistencies while taking between 6 and 6.5 s for each configuration.Moreover,positive feedback based on a subjective questionnaire from clinicians regarding the performance,acceptability,and efficiency of opt-LDT motivates us to present our results for regulatory approval.

Characteristics and Enlightenment of Health Informatics Education in American Universities

The demand for health information is increasing in China,and China has gradually paid attention to health informatics education.The successful experience of American health informatics education can effectively promote the development of health informatics education in China.This paper analyzes the main characteristics of health informatics education in American colleges and universities by literature survey and network survey,and concludes that Chinese colleges and universities should strengthen practical education,enhance teachers’strength,increase the form of educational projects,and perfect the curriculum content system.

The Theory of Bio-Medical Knowledge Integration(Ⅷ)──The Intrinsic Medical Informatics(IMI) and Meta-dimensions(MDs) of SNOMED

This paper presented the profile of Intrinsic Medical Informatics(IMI), which consists of Medical Cognition Informatics(MCI) and Organism Informatics(OI). MCI and OI are taken as two cornerstones of the Theory of BioMedical Knowledge Integration(BMKI). Additionally, so called Meta-dimension architecture of SNOMED is discussed in order to venture its context computing.

Education development and teaching reform of health informatics for Library and Information Science schools

The reform and development of health service mode require the support of health information.However,the lack of health information talents is the weakness of the current health service system in China.LIS schools should adapt to national strategies,social demands.

Enriching online access to health information for the public: Efforts from a medical library in China

Purpose: Disseminating medical and health information is a mission of a public medical library. This paper describes a practice of a medical library in providing online access to health information for the general public.Design/methodology/approach: A four-step workflow is developed to integrate and disseminate heterogeneous health information from medical associations. First, a raw data repository is developed to manage the original submissions from information providers.Second, each document in the raw data repository is represented in a standardized XML schema. Third, the medical terms are identified and manually annotated, enriching the semantics of health information. Lastly, all the semantically enriched XML documents are converted to HTMLs for online dissemination.Findings: A health information website, CHealth, was developed for Chinese speakers. It provides free online access for all without any login or IP constrains. CHealth is available at www.chealth.org.cn.Research limitations: The current workflow is time-consuming and labor-intensive due to the lack of information submission/exchange standard and commonly agreed-on consumer health terminology in Chinese.Originality/value: In this work, the target audience of the medical library has been extended from traditional academic/professional to the general public. Methodologies in library sciences have been combined with those in consumer health informatics in CHealth development.

Smart healthcare: making medical care more intelligent

With the development of information technology,the concept of smart healthcare has gradually come to the fore.Smart healthcare uses a new generation of information technologies,such as the internet of things(IoT),big data,cloud computing,and artificial intelligence,to transform the traditional medical system in an all-round way,making healthcare more efficient,more convenient,and more personalized.With the aim of introducing the concept of smart healthcare,in this review,we first list the key technologies that support smart healthcare and introduce the current status of smart healthcare in several important fields.Then we expound the existing problems with smart healthcare and try to propose solutions to them.Finally,we look ahead and evaluate the future prospects of smart healthcare.

Topic prevalence and trends of metaverse in healthcare:a bibliometric analysis

Metaverse technology is an advanced form of virtual reality and augmented technologies. It merges the digital world with the real world, thus benefitting healthcare services. Medical informatics is promising in the metaverse. Despite the increasing adoption of the metaverse in commercial applications, a considerable research gap remains in the academic domain, which hinders the comprehensive delineation of research prospects for the metaverse in healthcare. This study employs text-mining methods to investigate the prevalence and trends of the metaverse in healthcare;in particular, more than 34,000 academic articles and news reports are analyzed. Subsequently, the topic prevalence, similarity, and correlation are measured using topic-modeling methods. Based on bibliometric analysis, this study proposes a theoretical framework from the perspectives of knowledge, socialization, digitization, and intelligence. This study provides insights into its application in healthcare via an extensive literature review. The key to promoting the metaverse in healthcare is to perform technological upgrades in computer science, telecommunications, healthcare services, and computational biology. Digitization, virtualization, and hyperconnectivity technologies are crucial in advancing healthcare systems. Realizing their full potential necessitates collective support and concerted effort toward the transformation of relevant service providers, the establishment of a digital economy value system, and the reshaping of social governance and health concepts. The results elucidate the current state of research and offer guidance for the advancement of the metaverse in healthcare.

基于关联规则挖掘的健康信息学主题分析——以dHealth会议为例

本研究旨在析出当前健康信息学领域的研究主题和方向、研究热点和前沿问题,以2014—2020年共七年的dHealth会议文献作为研究对象,运用关联规则方法对会议文献的关键词进行分析,归纳总结出健康信息学的主要研究方向,并对相关主题的会议文献进行回溯介绍。分析结果表明,近年来dHealth会议文献在健康信息学领域有六个主要研究方向,包括标准与标准化研究、电子健康档案研究、互操作性研究、计算机技术与应用研究、移动医疗与远程医疗研究及临床信息学研究。研究结论有助于进一步明晰健康信息学的研究热点与主流话题,并探索未来发展的方向。

Translation in Data Mining to Advance Personalized Medicine for Health Equity

Personalized medicine is the development of “tailored” therapies that reflect traditional medical approaches with the incorporation of the patient’s unique genetic profile and the environmental basis of the disease. These individualized strategies encompass disease prevention and diagnosis, as well as treatment strategies. Today’s healthcare workforce is faced with the availability of massive amounts of patient- and disease-related data. When mined effectively, these data will help produce more efficient and effective diagnoses and treatment, leading to better prognoses for patients at both the individual and population level. Designing preventive and therapeutic interventions for those patients who will benefit most while minimizing side effects and controlling healthcare costs requires bringing diverse data sources together in an analytic paradigm. A resource to clinicians in the development and application of personalized medicine is largely facilitated, perhaps even driven, by the analysis of “big data”. For example, the availability of clinical data warehouses is a significant resource for clinicians in practicing personalized medicine. These “big data” repositories can be queried by clinicians, using specific questions, with data used to gain an understanding of challenges in patient care and treatment. Health informaticians are critical partners to data analytics including the use of technological infrastructures and predictive data mining strategies to access data from multiple sources, assisting clinicians’ interpretation of data and development of personalized, targeted therapy recommendations. In this paper, we look at the concept of personalized medicine, offering perspectives in four important, influencing topics: 1) the availability of “big data” and the role of biomedical informatics in personalized medicine, 2) the need for interdisciplinary teams in the development and evaluation of personalized therapeutic approaches, and 3) the impact of electronic medical record systems and clinical data warehouses on the field of personalized medicine. In closing, we present our fourth perspective, an overview to some of the ethical concerns related to personalized medicine and health equity.

The Theory of Bio-Medical Knowledge Integra tion(V)——The meta-dimensions and their combinations of the General Linkage/Modifiers of SNOMED

From the integrated view of cognitive and noetic sciences, a set of meta- dimensions and their com- binations, covering almost all of general linkage and modifiers of SNOMED, has been presented. Some examples for reasoning and operating for this set have been illustrated. Therefore the article has proved theoretically that it is possible to significantly increase the abilities of reasoning or operating and being- understood by computer in data mining of EMR, etc for a terminology system including relation (or linkage) or restriction (or modifier) items such as SNOMED. It is believed also the realizations of these tasks expected by this article are not difficult in technologic aspects for the modern software and data base technologies and the good IT engineers.

Exploration on the construction of medical service price general managements in Beijing

从国家对规范医疗服务价格（ 医价）管理的要求不断提高、现行管理方式存在的挑战等方面论述了在 大数据背景下,利用现代信息技术建立医疗服务价格管理平台,为政府价格管理、促进医院运营的必要性与可 行性;介绍了北京市医疗服务项目价格综合管理平台的特点：以顶层设计指导医价平台建设,依托大数据仓库 处理基础信息,设立业务与数据规范,构建统计分析辅助管理应用等;并进一步介绍了其阶段性建设成效.

Psychiatric electronic health records privacy in Jordan: A policy brief

Psychiatric health records are highly sensitive data which requires special policy to maintain its privacy,without affecting data accessibility.The current authors reviewed social,ethical and legal underpinnings for psychiatric electronic health records(EHR),and suggests a policy to maintain privacy and confidentiality of the psychiatric data,without affecting data accessibility.The purpose of this policy brief is to discuss and provide alternatives regarding psychiatric electronic health records privacy and information access.The current policy applied in Jordan still immature to ensure high levels of reliability,as the psychiatric data is openly accessed to the non-specialized personnel.Sensitive personal data policy is recommended in this paper with developing overriding mechanisms to counteract obstacles to data accessibility.

The Theory of Bio-Medical Knowledge Integration(Ⅵ)

This paper introduced the following new concepts:the cognitive goal, the cognitive goal for the declarative data of the patient records (PRs), The basic attributes of PR’s data at the sides of generation, construction and cognition, the generalized data creator (GDC), type Ⅰ to Ⅵ+ of GDC, the cognitive directions of data: forward direction and backward direction, the apparent cognitive orientation and inapparent cognitive orientation, the cognitive granularity difference principle between the natural intelligence and the artificial intelligence, the generalized variable(GVAR) and the generalized value(GVAL), the variable and value transitivity law(V-V transitivity law), the attribute-combination irreversibility between the concept abstracting and embodying, an open model of the launching engine of bio-medical cognition,

Opportunities for nurses in the era of electronic health records

Nursing leaders are currently faced with opportunities to advance nursing’s role in the use of electronic health records (EHRs). Nurse leaders can advance the design of EHRs with nurse informaticists to improve health outcomes of individual and populations of patients.

Standardization Contributes to preparation for Expo 2010 Shanghai

The task of standardization includes the formulation, organization, and supervision of standards, as well as the implementation of those standards. This paper outlines how standardization was illustrated, analyzed, and brought forward developmentally, while emphasizing implementation and supervision in accordance with the target and scope of the Expo 2010 Shanghai China Informatization.

新医改十年:中国医疗卫生信息化多元政策主体协同治理研究

医疗卫生信息化建设既是中国新一轮医疗卫生体制改革的建设重点,也是实现中国医疗卫生治理现代化的技术基础,但医疗卫生信息化建设内容系统、复杂,需要多部门高效合作、协同治理。基于新医改十年以来国家层面颁布的医疗卫生信息化政策文本,利用社会网络分析方法测度政策制定主体合作网络节点属性,构建政策主体合作“广度—深度”的二维矩阵,分析医疗卫生信息化建设中不同政策主体协同治理的角色演变规律。研究表明,医疗卫生信息化建设的政策主体日益多元,主体间协作关系日益复杂,但发挥其核心作用的机构有限,政策协作网络中心化特征显著;国家卫健委、国家中医药管理局、国家发改委、财政部、科技部、工信部、民政部、国家市场监督管理总局、教育部之间逐渐形成紧密合作闭环;政策主体角色变迁路径以渐进式演进为主,而突进式演进的直接动力主要源于上级政府关键政策文本的颁布。政策导向的学习与交流机制,是构建基于信任的府际关系、促进政策主体协同和实现医疗卫生治理现代化的重要前提。