Enabling Healthcare 4.0 for Pandemics最新文献

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Machine Learning: A Tool to Combat COVID‐19 机器学习:对抗COVID - 19的工具

Enabling Healthcare 4.0 for Pandemics

Pub Date : 2021-09-21 DOI: 10.1002/9781119769088.ch15

Shakti Arora, V. Athavale, Tanvi Singh

COVID-19 has become a global challenge and is threatening mankind. The global economy is in crisis due to a long tranche of partial to complete lockdown. Forecasting the number of COVID-19 cases is a challenge as cases are both symptomatic as well as asymptomatic, recurrence after recovery is another challenge. Careful data analysis is required to predict and estimate the number of affected cases as well as death ratio. During this pandemic situation, forecasting uncertainty is of utmost importance in decision making. In this chapter, authors have developed a model to predict the COVID-19 confirmed cases. The prediction is based on the data collected in different phases of lockdown in India. In this study, a model is developed using machine learning approaches based on the analysis of data of two Indian states Delhi and Maharashtra where maximum infected cases are found. This study is an attempt to help the decision-makers in better planning and actions. In this study, Neural Network (NN) and M5P model trees are applied to forecast the number of infected cases with each progressive day. Results suggest that the performance of the neural network-based model is slightly better than the M5P model tree in forecasting COVID-19 cases. © 2021 Scrivener Publishing LLC.

新冠肺炎疫情已成为全球性挑战，威胁着人类。由于长期的部分或完全封锁，全球经济处于危机之中。预测新冠肺炎病例数是一项挑战，因为病例既有症状，也有无症状，康复后复发是另一项挑战。预测和估计感染病例数以及死亡率需要仔细的数据分析。在这种大流行情况下，预测不确定性对决策至关重要。在本章中，作者开发了一个预测COVID-19确诊病例的模型。这一预测是基于在印度封锁的不同阶段收集的数据。在这项研究中，利用机器学习方法开发了一个模型，该模型基于对发现最多感染病例的两个印度邦德里和马哈拉施特拉邦的数据分析。本研究旨在帮助决策者更好地规划和行动。在本研究中，应用神经网络(NN)和M5P模型树来预测每天的感染病例数。结果表明，基于神经网络的模型在预测COVID-19病例方面的性能略优于M5P模型树。©2021 Scrivener Publishing LLC。

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引用次数: 0

Mathematical Insight of COVID‐19 Infection—A Modeling Approach COVID - 19感染a建模方法的数学洞察

Enabling Healthcare 4.0 for Pandemics

Pub Date : 2021-09-21 DOI: 10.1002/9781119769088.ch14

K. Arora, Pooja Khurana, Deepak Kumar, Bhanu Sharma

Application of mathematics has gotten progressively abundant in epidemic disease research. The complexity of disease is appropriate to quantitative methodologies as it gives difficulties and chances to new turns of events. Thusly, computational modeling demonstrating to epidemiology research by assisting with clarifying components and by giving quantitative expectations that can be approved. The ongoing extension of quantitative models tends to numerous inquiries with respect to Epidemic disease (COVID-19) inception, and treatment reactions and opposition. These models have allowed researchers to better understand the physical phenomena. Computational models can supplement exploratory and clinical investigations, yet additionally challenge flow standards, reclassify our comprehension of systems driving epidemiology and shape future research. © 2021 Scrivener Publishing LLC.

数学在传染病研究中的应用日益丰富。疾病的复杂性适合于定量方法，因为它给事态的新转变带来了困难和机会。因此，计算模型通过帮助澄清成分和给出可批准的定量期望来证明流行病学研究。定量模型的持续扩展倾向于对流行病(COVID-19)的开始以及治疗反应和反对进行大量查询。这些模型使研究人员能够更好地理解物理现象。计算模型可以补充探索性和临床研究，但也可以挑战流量标准，重新分类我们对驱动流行病学的系统的理解，并塑造未来的研究。©2021 Scrivener Publishing LLC。

引用次数: 0

Rapid Forecasting of Pandemic Outbreak Using Machine Learning 使用机器学习快速预测流行病爆发

Enabling Healthcare 4.0 for Pandemics

Pub Date : 2021-09-21 DOI: 10.1002/9781119769088.ch4

Sujata Chauhan, M. Singh, P. Garg

Humans have faced a number of pandemics since the dawn of civilization, but today what we are facing is an invisible enemy novel COVID-19, causing the pandemic globally at an alarming rate, bringing a devastating effect on our lives and impacting our economy drastically. The infection in humans by COVID-19 was thought to be originally from bats perhaps as zoonotic agent (from animal to human) but the rapid increase in the figure of cases in Wuhan city and globally even after shutting the market off and quarantine whole city, indicated an alternative mode of transmission from human-to-human which is rarely observed in nature. The main objective of this chapter is to predict a rapid forecasting of pandemic outbreak using machine learning approaches. The chapter is based on a preliminary estimation about the disease, spread of disease across the globe, the possible ways of treatment, and prevention in its outbreak which makes use of technologies like machine learning which may prove beneficial to save the human race from pandemics like COVID19 in the future. © 2021 Scrivener Publishing LLC.

自文明诞生以来，人类面临过多次大流行，但今天我们面临的是一个看不见的敌人——新型冠状病毒病，它以惊人的速度在全球范围内造成大流行，给我们的生活带来毁灭性影响，并严重影响我们的经济。人类感染COVID-19被认为最初来自蝙蝠，可能是人畜共患媒介(从动物到人类)，但即使在关闭市场和隔离整个城市之后，武汉市和全球病例数的迅速增加表明，在自然界中很少观察到人与人之间的另一种传播方式。本章的主要目标是使用机器学习方法预测大流行爆发的快速预测。这一章是基于对疾病的初步估计，疾病在全球的传播，可能的治疗方法，以及在疫情爆发时的预防，利用机器学习等技术，这可能有助于在未来拯救人类免受covid - 19等流行病的侵害。©2021 Scrivener Publishing LLC。

引用次数: 3

Healthcare System 4.0 Perspectives on COVID‐19 Pandemic 医疗保健系统4.0对COVID - 19大流行的看法

Enabling Healthcare 4.0 for Pandemics

Pub Date : 2021-09-21 DOI: 10.1002/9781119769088.ch2

R. Rayan, I. Zafar, I. Romash

COVID-19 has generated needs for health tools, medications, and applications in information technology. Industry 4.0 is about techniques like artificial intelligence (AI) or robots as tools that are designed to carry improvement in responding to the changing world. According to scientific data, industry 4.0 offers novel insights and solutions to national and international health agencies. Healthcare system 4.0 (HCS 4.0), a part of the fourth industrial transformation, could meet demands in the disaster of COVID-19. There are valuable HCS 4.0 techniques that could assist in controlling and managing the pandemic via detecting and diagnosing COVID- 19 and other associated issues. For instance, HCS 4.0 could meet the demands for face masks, gloves, and gather information for health sectors to adequately address the infected cases with COVID-19. It is also important to deliver daily updates about infected cases, including demographics via surveillance systems. Applying such techniques adequately could improve public health communication and education. Ultimately, the techniques for HCS 4.0 could offer many novel interventions for addressing local and universal catastrophes in health. This chapter explores the leading HCS 4.0 techniques that could address this pandemic, highlighting real-world applications, opportunities, challenges, and future insights. © 2021 Scrivener Publishing LLC.

COVID-19催生了对卫生工具、药物和信息技术应用的需求。工业4.0是指人工智能(AI)或机器人等技术作为工具，旨在应对不断变化的世界。根据科学数据，工业4.0为国家和国际卫生机构提供了新颖的见解和解决方案。医疗系统4.0 (HCS 4.0)是第四次产业转型的一部分，可以满足COVID-19灾难的需求。有一些有价值的HCS 4.0技术可以通过检测和诊断COVID- 19和其他相关问题来帮助控制和管理大流行。例如，HCS 4.0可以满足对口罩和手套的需求，并为卫生部门收集信息，以充分解决COVID-19感染病例。每天提供感染病例的最新情况也很重要，包括通过监测系统提供人口统计数据。充分应用这些技术可以改善公共卫生宣传和教育。最终，HCS 4.0的技术可以为解决当地和普遍的健康灾难提供许多新的干预措施。本章探讨了可以应对这一流行病的领先HCS 4.0技术，重点介绍了现实世界的应用、机遇、挑战和未来的见解。©2021 Scrivener Publishing LLC。

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引用次数: 1

Multi‐Purpose Robotic Sensing Device for Healthcare Services 用于医疗保健服务的多用途机器人传感装置

Enabling Healthcare 4.0 for Pandemics

Pub Date : 2021-09-21 DOI: 10.1002/9781119769088.ch12

Das HirakRanjan, Bhatia Dinesh, A. Patowary, Animesh Mishra

The whole world at present is under the grasp of a pandemic termed as COVID-19. The World Health Organization (WHO) guidelines suggest that the social distancing norms are followed with contactless operations as far as possible. Therefore, the population around the world is turning towards efficient modes of operating the daily work with minimal human contact. To contain the spread of the novel coronavirus or COVID-19, it is important and suitable to deploy machinery for operating in conditions wherever social distancing is required. The multipurpose robot makes it feasible to minimize human contact and carry out operations without the risk of the spread of the virus. This chapter aims at the fabrication of a robot that can have multiple utilities and is employed in different areas as per the requirement of the user. © 2021 Scrivener Publishing LLC.

当前，全世界正处于一场名为COVID-19的大流行之中。世界卫生组织(世卫组织)的指导方针建议，尽可能在非接触式手术中遵守社交距离规范。因此，世界各地的人们正在转向以最少的人接触的高效方式来开展日常工作。为遏制新型冠状病毒或COVID-19的传播，重要的是，在需要保持社交距离的条件下部署机器是合适的。多用途机器人可以最大限度地减少与人的接触，并在没有病毒传播风险的情况下进行手术。本章的目的是制造一个机器人，可以有多种用途，并根据用户的要求在不同的领域使用。©2021 Scrivener Publishing LLC。

引用次数: 0

Emerging Techniques for Handling Pandemic Challenges 应对流行病挑战的新兴技术

Enabling Healthcare 4.0 for Pandemics

Pub Date : 2021-09-21 DOI: 10.1002/9781119769088.ch10

Ankur Gupta, P. Garg

The world right now is dealing with a nightmare in the form of Corona virus disease. COVID-19 has been declared a pandemic by the WHO. It’s an infectious disease caused by virus called SARS-CoV-2. The symptoms of the disease range from fever, dry cough, headaches to difficulty in breathing. Technology has been making it out lives easier and how. The healthcare system also incorporates technology everywhere. We can use latest technologies to deal with crisis situations such as pandemic. Remote healthcare monitoring is the process of monitoring patients in a non-clinical environment. The patients can be provided with sensors and wearable’s to monitor them from afar. The devices range from wearable health monitors to fit bits. Artificial Intelligence is the future, everyone says. With help of technology, devices can check that people are maintaining social distancing and have their masks on. The data collected can be used to make people aware during a pandemic situation. It can be psychologically disturbing and stir up all sorts of feelings, like unreasonable fear and stress. Online counseling also proves helpful to those who shy way in going to hospitals to discuss issues such as depression. It also breaks the barrier of stigma among the patients. © 2021 Scrivener Publishing LLC.

目前，世界正在应对冠状病毒疾病的噩梦。世界卫生组织宣布新冠肺炎为大流行。这是一种由SARS-CoV-2病毒引起的传染病。这种疾病的症状包括发烧、干咳、头痛和呼吸困难。科技让我们的生活变得更容易。医疗保健系统也无处不在地融合了技术。我们可以利用最新技术来应对流行病等危机情况。远程医疗监控是在非临床环境中监控患者的过程。病人可以配备传感器和可穿戴设备，从远处监测他们。这些设备包括从可穿戴式健康监测器到可穿戴式比特。每个人都说人工智能是未来。在技术的帮助下，设备可以检查人们是否保持社交距离并戴上口罩。收集的数据可用于在大流行期间使人们有所认识。它会在心理上令人不安，激起各种各样的感觉，比如不合理的恐惧和压力。对于那些羞于去医院讨论抑郁症等问题的人来说，在线咨询也被证明是有帮助的。这也打破了患者之间的耻辱障碍。©2021 Scrivener Publishing LLC。

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引用次数: 0

Emerging Technologies for Handling Pandemic Challenges 应对流行病挑战的新兴技术

Enabling Healthcare 4.0 for Pandemics

Pub Date : 2021-09-21 DOI: 10.1002/9781119769088.ch6

D. Karthika, K. Kalaiselvi

Most pandemic burdens, for instance, genuine extreme respiratory conditions, pandemic flu start in animals, are invited on utilizing contaminations and are pushed to ascend by strategies for ecological, direct, or budgetary changes. In this, how mechanical and self-proceeding with structures and quick wearable enhancement and help social protection transport and the restorative administrations gathering of workers for the term of the COVID-19 pandemic are presented. For instance, mechanized and telerobotic structures altogether limit the danger of powerful issue transmission to forefront human administrations people through creation it possible to triage, survey, screen, and treat casualties from a protected division great deal occurrences of the recognize the clinical, planning, and science systems get together to resource the restorative administration’s structure, therapeutic administrations workers, and society all through the propelled disaster are presented. This section centers around computational strategies and real factors, artificial Intelligence (AI) and Big Data can help in dealing with the gigantic, unprecedented proportion of records got from open health surveillance, consistent plague flare-ups watching, vogue right now tossing/deciding, common condition briefing and invigorating from authoritative establishments and animals, and prosperity office utilization of information. © 2021 Scrivener Publishing LLC.

大多数流行病负担，例如，真正的极端呼吸条件，大流行性流感在动物中开始，都是利用污染引起的，并被生态，直接或预算变化的战略所推动。在此基础上，介绍了在新冠肺炎大流行期间，机械和自行进的结构和快速可穿戴增强以及帮助社会保障运输和工人的恢复性行政集会。例如，机械化和远程机器人结构共同限制了强大的问题传播到前沿的危险人类管理人员通过创造可以从一个受保护的部门进行分类，调查，筛选和治疗伤亡人员很多情况下认识到临床，计划和科学系统聚集在一起为恢复性管理结构提供资源，治疗管理人员，而整个社会都是通过推动灾难来呈现的。本节以计算策略和现实因素为中心，人工智能和大数据可以帮助处理从公开卫生监测、持续监测鼠疫突发事件、时尚即时切换/决定、权威机构和动物的常见情况简报和激励、繁荣办公信息利用等方面获得的巨大的、前所未有的记录。©2021 Scrivener Publishing LLC。

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引用次数: 0

Unfolding the Potential of Impactful Emerging Technologies Amid COVID‐19 在2019冠状病毒病期间发挥有影响力的新兴技术的潜力

Enabling Healthcare 4.0 for Pandemics

Pub Date : 2021-09-21 DOI: 10.1002/9781119769088.ch7

N. Rouf, Aatif Kaisar Khan, M. B. Malik, Akib Mohi Ud Din Khanday, Nadia Gul

引用次数: 1

Advances in Technology: Preparedness for Handling Pandemic Challenges 技术进步:应对大流行挑战的准备

Enabling Healthcare 4.0 for Pandemics

Pub Date : 2021-09-21 DOI: 10.1002/9781119769088.ch8

Shweta Sinha, V. Thada

High transmissibility and lack of effective vaccine have made the control of disease spread a challenge, and eventually, they take the form of a pandemic. The uncontrollable spread of virus creates challenges not only for the social or health front but also on the global economy. This chapter discusses the social, health and economic difficulties due to pandemic. The claims are validated with reference to the present-day epidemic the COVID-19. Technology promises to make life easier. The role of technology in government coordinated efforts to the response and preparedness is discussed in the chapter. Forecasting the spread pattern helps in readiness to handle the severity. Undoubtedly the technological advancements have led several changes to the society leading to a comfortable lifestyle even during the challenging times. The discussion here outlines the role of these advancements during the time of the pandemic. As digital technology intervenes to control the disastrous effect on humankind, it simultaneously introduces several challenges that are highlighted in the chapter. © 2021 Scrivener Publishing LLC.

高传染性和缺乏有效疫苗使控制疾病传播成为一项挑战，并最终以大流行的形式出现。病毒无法控制的蔓延，不仅给社会健康带来挑战，也给全球经济带来挑战。这一章讨论了流行病造成的社会、卫生和经济困难。这些说法与当前的COVID-19流行病有关。科技承诺让生活更轻松。本章讨论了技术在政府协调应对和准备工作中的作用。预测传播模式有助于做好应对疫情严重性的准备。毫无疑问，技术进步给社会带来了一些变化，即使在充满挑战的时代，也能带来舒适的生活方式。这里的讨论概述了这些进展在大流行期间的作用。当数字技术介入控制对人类的灾难性影响时，它同时引入了本章强调的几个挑战。©2021 Scrivener Publishing LLC。

引用次数: 1

COVID‐19 and Machine Learning Approaches to Deal With the Pandemic COVID - 19和机器学习方法应对大流行

Enabling Healthcare 4.0 for Pandemics

Pub Date : 2021-09-21 DOI: 10.1002/9781119769088.ch1

Sapna Juneja, Abhinav Juneja, V. Bali, Vishal Jain

The whole world is struggling to live with COVID-19 and even a single step of technology revolution can help in dealing with this pandemic. Artificial Intelligence and Machine Learning approaches are being used by the researchers around the globe to completely understand and address this situation. In this Corona crisis, companies are trying to implement this AI and ML techniques in various fields ranging from manufacturing, resource management, remote monitoring etc. On the other hand, ML approach is being used by the researchers for supporting healthcare related issues arisen due to COVID-19. © 2021 Scrivener Publishing LLC.

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全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

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Enabling Healthcare 4.0 for Pandemics

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