LEADER 11441nam 22006373 450 001 9911006696603321 005 20230411080245.0 010 $a1-83724-477-4 010 $a1-5231-5539-6 010 $a1-83953-580-6 035 $a(MiAaPQ)EBC30476721 035 $a(Au-PeEL)EBL30476721 035 $a(OCoLC)1375545031 035 $a(NjHacI)9926411274800041 035 $a(BIP)086633480 035 $a(CKB)26411274800041 035 $a(EXLCZ)9926411274800041 100 $a20230411d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDigital Twin Technologies for Healthcare 4. 0 205 $a1st ed. 210 1$aStevenage :$cInstitution of Engineering & Technology,$d2023. 210 4$dİ2022. 215 $a1 online resource (217 pages) 225 1 $aHealthcare Technologies Series 311 08$a1-83953-579-2 327 $aIntro -- Title -- Copyright -- Contents -- About the editors -- 1 Introduction: digital twin technology in healthcare -- 1.1 Introduction -- 1.2 Digital twin - background study -- 1.3 Research on digital twin technologies -- 1.4 Digital twin sectors in healthcare -- 1.4.1 Digital patient -- 1.4.2 Pharmaceutical industry -- 1.4.3 Hospital -- 1.4.4 Wearable technologies -- 1.5 Challenges and issues in implementation -- 1.5.1 Trust -- 1.5.2 Security and privacy -- 1.5.3 Standardization -- 1.5.4 Diversity and multisource -- References -- 2 Convergence of Digital Twin, AI, IOT, and machine learning techniques for medical diagnostics -- 2.1 Introduction -- 2.2 DT technology -- 2.2.1 Steps in DT creation -- 2.2.2 DT types and functions -- 2.3 DT and its supporting technologies - AI, Cloud computing, DL, Big Data analytics, ML, and IoT -- 2.4 DT integration with other technologies for medical diagnosis and health management -- 2.5 DT technology and its application -- 2.5.1 DT application in manufacturing industry -- 2.5.2 Applications of DT in automotive & -- aerospace -- 2.5.3 Medicine diagnosis and device development -- 2.5.4 Wind twin technology -- 2.6 Conclusion -- References -- 3 Application of digital twin technology in model-based systems engineering -- 3.1 Evolution of DTT -- 3.2 Basic concepts of DTT -- 3.3 DTT implementation in power system -- 3.3.1 Characteristics of DTT in power systems -- 3.4 Power system network modeling using DTT -- 3.4.1 Model-based approach -- 3.4.2 Data-driven approach -- 3.4.3 Combination of both -- 3.5 Integration of power system with DTT -- 3.6 Future scope of DTT in power systems -- 3.7 Conclusion -- References -- 4 Digital twins in e-health: adoption of technology and challenges in the management of clinical systems -- 4.1 Introduction -- 4.2 Digital twin -- 4.3 Evolution of healthcare services. 327 $a4.4 Elderly medical services and demands -- 4.5 Cloud computing -- 4.6 Cloud computing DT in healthcare -- 4.6.1 Use cases -- 4.7 Digital healthcare modeling process -- 4.8 Cloud-based healthcare facility platform -- 4.9 Applications of DT technology -- 4.9.1 Cardiovascular application -- 4.9.2 Cadaver high temperature -- 4.9.3 Diabetes meters -- 4.9.4 Stress monitoring -- 4.10 Benefits of DT technology -- 4.10.1 Remote monitoring -- 4.10.2 Group cooperation -- 4.10.3 Analytical maintenance -- 4.10.4 Transparency -- 4.10.5 Future prediction -- 4.10.6 Information -- 4.10.7 Big data analytics and processing -- 4.10.8 Cost effectiveness -- 4.11 DT challenges in healthcare -- 4.11.1 Cost effectiveness -- 4.11.2 Data collection -- 4.11.3 Data protection -- 4.11.4 Team collaboration -- 4.11.5 Monitoring -- 4.11.6 Software maintenance and assurance -- 4.11.7 Regulatory complications -- 4.11.8 Security and privacy-related issues -- 4.11.9 Targets of attackers -- 4.12 Conclusion -- References -- 5 Digital twin and big data in healthcare systems -- 5.1 Introduction -- 5.1.1 Working of DT technology -- 5.2 Need for DT and big data in healthcare -- 5.3 DT and big data benefits for healthcare -- 5.3.1 Monitoring of patients -- 5.3.2 Individualized medical care -- 5.3.3 Patient individuality and freedom -- 5.4 Applications of DT in healthcare -- 5.4.1 Diagnosis and decision support -- 5.4.2 Patient monitoring -- 5.4.3 Drug and medical device development -- 5.4.4 Personalized medicine -- 5.4.5 Medical imaging and wearables -- 5.5 Enabling technologies for DT and data analytics in healthcare -- 5.5.1 Technologies for DT in healthcare -- 5.5.2 Technologies for data analytics in healthcare -- 5.6 Research challenges of DT and big data in healthcare -- 5.6.1 Problem complexities and challenges -- 5.6.2 Research challenges for DT in healthcare. 327 $a5.6.3 Useful information -- 5.7 Future research directions -- 5.8 Conclusion -- References -- 6 Digital twin data visualization techniques -- 6.1 Introduction - twin digital -- 6.2 Invention of DT -- 6.2.1 Function of DT technology -- 6.2.2 What problems has it solved? -- 6.3 DT types -- 6.3.1 Parts twinning -- 6.3.2 Product twinning -- 6.3.3 System twinning -- 6.3.4 Process twinning -- 6.4 When to use -- 6.5 Design DT -- 6.5.1 Digital data -- 6.5.2 Models -- 6.5.3 Linking -- 6.5.4 Examples -- 6.5.5 How has it impacted the industry? -- 6.5.6 DT usage -- 6.6 DT technology's characteristics -- 6.6.1 Connectivity -- 6.6.2 Homogenization -- 6.6.3 Reprogrammable -- 6.6.4 Digital traces -- 6.6.5 Modularity -- 6.7 Twin data to data -- 6.7.1 Requirements for obtaining complete data -- 6.7.2 Requirements on knowledge mining -- 6.7.3 Data fusion in real time -- 6.7.4 Data interaction in real time -- 6.7.5 Optimization in phases -- 6.7.6 On-demand data usage -- 6.7.7 Data composed of DTs -- 6.8 Data principles for DTs -- 6.8.1 Principle of complementary -- 6.8.2 The principle of standardization -- 6.8.3 The principle of timeliness -- 6.8.4 The association principle -- 6.8.5 Fusion principle -- 6.8.6 Information growth principle -- 6.8.7 The principle of servitization -- 6.9 DTD methodology -- 6.9.1 Information gathering for the DT -- 6.9.2 Data storage of DTs -- 6.9.3 DT data interaction -- 6.9.4 Association of DT data -- 6.9.5 Fusion of data from DTs -- 6.9.6 Data evolution in the DT -- 6.9.7 Data servitization for the DT -- 6.9.8 DT data's key enabler technologies -- 6.9.9 Advantages of DT -- 6.9.10 Disadvantages of DT -- 6.10 Conclusion -- References -- 7 Healthcare cyberspace: medical cyber physical system in digital twin -- 7.1 Introduction -- 7.2 Cyber physical systems -- 7.3 Digital twin -- 7.4 DT in healthcare -- 7.4.1 Patient monitoring using DT. 327 $a7.4.2 Operational efficiency in hospital using DT -- 7.4.3 Medical equipment and DT -- 7.4.4 DT in device development -- 7.5 Applications of DT in healthcare -- 7.5.1 Patient monitoring using DT -- 7.5.2 Medical wearables -- 7.5.3 Medical tests and procedures -- 7.5.4 Medical device optimization -- 7.5.5 Drug development -- 7.5.6 Regulatory services -- 7.6 DT framework in healthcare -- 7.6.1 Prediction phase -- 7.6.2 Monitoring phase -- 7.6.3 Comparison phase -- 7.7 Cyber resilience in healthcare DT -- 7.8 Cyber physical system and DT -- 7.8.1 Mapping in CPS and DTs -- 7.8.2 Unit level -- 7.8.3 System level -- 7.8.4 SoS level -- 7.9 Advantages of DT -- 7.10 Summary -- References -- 8 Cloud security-enabled digital twin in e-healthcare -- 8.1 Introduction -- 8.2 E-healthcare and cloud security-enabled digital twin -- 8.2.1 ICT facilities -- 8.2.2 Cloud security-enabled digital twin -- 8.3 Cloud healthcare service platform with digital twin -- 8.3.1 Wearable technologies -- 8.3.2 Pharmaceutical industry -- 8.3.3 Digital patients -- 8.3.4 Hospital -- 8.4 Security and privacy requirements for cloud security-enabled digital twin in e-healthcare -- 8.4.1 Security requirements for cloud security-enabled digital twin in e-healthcare -- 8.4.2 Privacy requirements for cloud security-enabled digital twin in e-healthcare -- 8.5 Challenges in cloud-based digital twin in e-healthcare -- 8.6 Conclusion -- References -- 9 Digital twin in prognostics and health management system -- 9.1 Introduction -- 9.2 Pile of DT -- 9.2.1 Digital mirror (physical infrastructure) -- 9.2.2 Digital data flow -- 9.2.3 Digital virtual thread -- 9.3 A complete DT model -- 9.4 Phases of DT development -- 9.4.1 Developing a simulation -- 9.4.2 Fusion of data -- 9.4.3 Interaction -- 9.4.4 Service -- 9.5 DT applications in healthcare -- 9.5.1 Healthcare system. 327 $a9.5.2 Recovery of the patient -- 9.5.3 Precision medicine -- 9.5.4 Research in pharmaceutical development -- 9.5.5 Drug administration -- 9.5.6 Disease treating ways -- 9.6 Challenges in DT implementation -- 9.6.1 Infrastructure for information technology -- 9.6.2 Data utilization -- 9.6.3 Consistent modeling -- 9.6.4 Modeling of domains -- 9.7 Role of DT in healthcare -- 9.7.1 Medicine that is tailored to the individual -- 9.7.2 Development of virtual organs -- 9.7.3 Medicine based on genomic data -- 9.7.4 Healthcare apps -- 9.7.5 Surgery scheduling -- 9.7.6 Increasing the effectiveness of healthcare organizations -- 9.7.7 Improving the experience of caregivers -- 9.7.8 Increasing productivity -- 9.7.9 Critical treatment window shrinking -- 9.7.10 Healthcare delivery system based on value -- 9.7.11 Rapid hospital erection -- 9.7.12 Streamlining interactions in call center -- 9.7.13 Development of pharmaceuticals and medical devices -- 9.7.14 Detecting the dangers in drugs -- 9.7.15 Simulating the new production lines -- 9.7.16 Improving the device availability -- 9.7.17 Post-sales surveillance -- 9.7.18 Human variability simulation -- 9.7.19 A lab's DT -- 9.7.20 Improving drug distribution -- 9.8 Benefits -- References -- 10 Deep learning in Covid-19 detection and diagnosis using CXR images: challenges and perspectives -- 10.1 Introduction -- 10.1.1 CNN -- 10.1.2 ANN -- 10.1.3 RNN -- 10.1.4 LSTM -- 10.1.5 GRU -- 10.1.6 Deep autoencoders -- 10.1.7 Deep Boltzmann's machine -- 10.2 Related work -- 10.2.1 Detection/localization -- 10.2.2 Segmentation -- 10.2.3 Registration -- 10.2.4 Classification -- 10.2.5 Application -- 10.3 Proposed model -- 10.3.1 Image pre-processing -- 10.3.2 Data augmentation -- 10.3.3 CNN with transfer learning -- 10.3.4 ChestXRay20 dataset -- 10.4 Experiments and result discussion -- Case 1: Covid-19 vs. healthy. 327 $aCase 2: Covid-19 vs. pneumonia. 330 $aThis book discusses digital twin technologies for applications in the healthcare system. The book also addresses the various research perspectives and challenges in implementation of digital twin technology in terms of data analysis, cloud management and data privacy issues. 410 0$aHealthcare Technologies Series 606 $aDigital twins (Computer simulation) 606 $aMedical telematics 606 $aArtificial intelligence$xMedical applications 615 0$aDigital twins (Computer simulation) 615 0$aMedical telematics. 615 0$aArtificial intelligence$xMedical applications. 676 $a610.285 700 $aDhanaraj$b Rajesh Kumar$01380450 701 $aMurugesan$b Santhiya$01823614 701 $aBalusamy$b Balamurugan$01340583 701 $aBalas$b Valentina E$01823615 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911006696603321 996 $aDigital Twin Technologies for Healthcare 4. 0$94390382 997 $aUNINA LEADER 04633nam 2200637I 450 001 9910971701903321 005 20191015135049.0 010 $a9781787690639 010 $a1787690636 010 $a9781787690615 010 $a178769061X 035 $a(CKB)4100000009037657 035 $a(MiAaPQ)EBC5850021 035 $a(UtOrBLW)9781787690615 035 $a(Perlego)954124 035 $a(EXLCZ)994100000009037657 100 $a20191018h20192019 uy 0 101 0 $aeng 135 $aurun||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aInformed learning applications $einsights from research and practice /$fedited by Kim L. Ranger 205 $a1st ed. 210 1$aBingley, England :$cEmerald Publishing,$d[2019] 210 4$dİ2019 215 $a1 online resource (156 pages) 225 0 $aAdvances in librarianship,$x0065-2830 ;$vvolume 46 300 $aIncludes index. 311 08$a9781787690646 311 08$a1787690644 311 08$a9781787690622 311 08$a1787690628 327 $aThe six frames in schools: Practices from Taiwan -- Simultaneous learning about research and Filmmaking: Informed learning and research guides -- Beyond information literacy: Rethinking approaches to the college public speaking curriculum -- Ways of learning of information professionals: Concepts, roles, and strategies -- Relational liaising to integrate informed learning into the disciplinary classroom -- Academic librarians as informed learning developers -- Information literacy (IL) "Without borders": The future of IL education -- Power and resistance in informed learning. 330 $aInformed Learning Applications: Insights from Research and Practice is the latest volume of rigorous research in the Advances in Librarianship series. Edited by experienced librarian Kim L. Ranger, the eight contributions to this volume describe various practices using and extending Christine Bruce's informed learning theory from a range of educational spaces, from schools to universities. Chen and Chen address integrated information literacy instruction in Taiwanese elementary schools by joining the Big6 model, inquiry-based learning, and Bruce's Six Frames. Woods and Cummins apply universal design in teaching first-year university students about the research process within the discipline of documentary filmmaking using library guides. Tucker blends informed learning with Meyer and Land's threshold concepts to redesign master's courses and uses information experience to assess students' transformed learning experiences and relationships with information. Leek and Brown train university speech center peer tutors and recommend revising public speaking communication curricula. Ranger creates a model of relational liaising by applying Bakhtinian leadership principles to academic librarianship and gives examples that combine informed learning and scholarly communication. Fundator and Maybee transform the role of librarians in higher education to "informed learning developers." Cunningham uses blended models that represents stakeholders' information literacy conceptions and perceptions of their information context to promote learning in an international school community. Whitworth and Webster observe postgraduate students as they negotiate power and authority through resistance in their online communication practices. Informed Learning Applications focuses on integrating approaches to learning, featuring librarian praxis and collaboration with disciplinary instructors. It is the ideal read for academic librarians and researchers looking to explore how to facilitate learning. 410 0$aAdvances in librarianship ;$vv. 46$x0065-2830$w(OCoLC)1461209 606 $aInformation literacy 606 $aLearning 606 $aLibraries and the Internet 606 $aInformation services$xUser education 606 $aLanguage Arts & Disciplines$xLibrary & Information Science$xAdministration & Management$2bisacsh 606 $aLibrary & information services$2bicssc 615 0$aInformation literacy. 615 0$aLearning. 615 0$aLibraries and the Internet. 615 0$aInformation services$xUser education. 615 7$aLanguage Arts & Disciplines$xLibrary & Information Science$xAdministration & Management. 615 7$aLibrary & information services. 676 $a028.7 702 $aRanger$b Kim L. 801 0$bUtOrBLW 801 1$bUtOrBLW 906 $aBOOK 912 $a9910971701903321 996 $aInformed learning applications$94462210 997 $aUNINA