Remote patient monitoring: a computational perspective in healthcare
This book provides a multidisciplinary overview of the design and implementation of systems for remote patient monitoring and healthcare. Readers are guided through the components of such a system and shown how they could be integrated into a coherent framework for deployment in practice. The book e...
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Gistrup, Denmark
River Publishers
[2023]
|
| Schriftenreihe: | River Publishers rapids series in biotechnology and medical research
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| Schlagworte: | |
| Online-Zugang: | FHI01 Volltext Taylor & Francis |
| Zusammenfassung: | This book provides a multidisciplinary overview of the design and implementation of systems for remote patient monitoring and healthcare. Readers are guided through the components of such a system and shown how they could be integrated into a coherent framework for deployment in practice. The book ends with a discussion of case studies to provide practical examples and design methods for remote healthcare systems with different needs. This book contains information that will be helpful to undergraduate and postgraduate students, academic and professional researchers, and individuals who employ computational intelligence. By presenting new models of care and support, AI in medicine is having an impact on the entire value chain of clinical practice and the patient care delivery system. This is especially evident in telemedicine breakthroughs, where applications of AI are utilized to assist, complement, or create new forms of remote healthcare. Through the use of communications technology, telemedicine enables medical professionals to examine, diagnose, and treat patients remotely. Now, the technology might also integrate online diagnostics, etc., to increase the effectiveness of the healthcare system and enhance patient outcomes. By enabling elderly people to live independently, technological advancements in fields like remote patient monitoring (RPM) systems can revolutionize senior care. Medical diagnosis will improve, and remote patient monitoring will become simpler thanks to artificial intelligence. The resistance of many patients and doctors to using the telemedicine idea for medical visits will probably be overcome by AI automation |
| Beschreibung: | 1 Online-Ressource (xi, 82 Seiten) Illustrationen, Diagramme |
| ISBN: | 9788770040242 8770040249 9781003810247 1003810241 9781032627991 1032627999 9781003810339 1003810330 |
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| 505 | 8 | |a Preface ix About the Authors xi 1 Future of Remote Patient Monitoring with AI: An Overview 1 1.1 Introduction 1 1.2 Impact of AI on RPM 3 1.3 AI in RPM: Challenges and Trends 6 1.4 Conclusion 9 2 Remote Patient Monitoring by Artificial Intelligence: Bringing a Paradigm Shift to Healthcare 17 2.1 Introduction 18 2.2 Attributes of SHM and IoMT 20 2.3 The IoTM and SHM Frameworks 20 2.4 Data Security in SHM 23 2.5 Remote Heart Rate Tracking 23 2.6 Sensor Enabled IoT-based Devices 24 2.7 Superior Medical Technology 24 2.8 Smart Health Monitoring 25 2.9 Service Coordination in Healthcare 25 2.10 Conclusion 26 3 Advancement in AI Enables Hospital Movement at Home 31 3.1 Introduction 31 3.2 ⁰́₋Health Smart Home⁰́₊ 33 3.3 HSH Applications 36 3.4 Driving Forces for Health Smart Homes 37 3.5 Advanced Technologies 39 3.6 Demonstration Space, Pilot Projects, | |
| 505 | 8 | |a and Full-Scale Housing 39 3.7 Design of a Smart Home Care System for Rural Elderly Based on AI 40 3.8 Conclusion 41 4 Obstacles and Complexity in AI Embedded Remote Health Monitoring 47 4.1 Introduction 48 4.2 Healthcare With AI 48 4.3 The Positive Effects of AI in Healthcare 49 4.4 Using AI to Improve Healthcare in Areas Such as Illness Prevention, Detection, and Treatment 50 4.5 Background Theory for AI and ML, with Instances in the Healthcare Industry 51 4.6 Improved Patient Care via Machine Learning and Increased Provider⁰́₃Patient Communication 52 4.7 Oncology, Big Data, and AI 52 4.8 Intelligent Digital Pathology with Deep Learning 53 4.9 Smart Health Data Analytics for Better Healthcare System Administration, Patient Outcomes, Scientific Discovery, | |
| 505 | 8 | |a and New Treatment Methods 53 4.10 Artificial Intelligence (AI) Applications in Orthopedics 53 4.11 Conclusion 56 5 Telehealth using Machine learning 65 5.1 Introduction 66 5.2 Related works 67 5.3 System of Watchful Waiting: A Proposed Scheme 69 5.4 Methodology 71 5.5 Hardware Information 74 5.6 Description of the Program 75 5.7 Conclusion 76 Index 81 | |
| 520 | 3 | |a This book provides a multidisciplinary overview of the design and implementation of systems for remote patient monitoring and healthcare. Readers are guided through the components of such a system and shown how they could be integrated into a coherent framework for deployment in practice. The book ends with a discussion of case studies to provide practical examples and design methods for remote healthcare systems with different needs. This book contains information that will be helpful to undergraduate and postgraduate students, academic and professional researchers, and individuals who employ computational intelligence. By presenting new models of care and support, AI in medicine is having an impact on the entire value chain of clinical practice and the patient care delivery system. This is especially evident in telemedicine breakthroughs, where applications of AI are utilized to assist, complement, or create new forms of remote healthcare. Through the use of communications technology, telemedicine enables medical professionals to examine, diagnose, and treat patients remotely. Now, the technology might also integrate online diagnostics, etc., to increase the effectiveness of the healthcare system and enhance patient outcomes. By enabling elderly people to live independently, technological advancements in fields like remote patient monitoring (RPM) systems can revolutionize senior care. Medical diagnosis will improve, and remote patient monitoring will become simpler thanks to artificial intelligence. The resistance of many patients and doctors to using the telemedicine idea for medical visits will probably be overcome by AI automation | |
| 653 | 0 | |a Patient monitoring | |
| 653 | 0 | |a Telecommunication in medicine | |
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| 653 | 0 | |a Intelligence artificielle en médecine | |
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| contents | Preface ix About the Authors xi 1 Future of Remote Patient Monitoring with AI: An Overview 1 1.1 Introduction 1 1.2 Impact of AI on RPM 3 1.3 AI in RPM: Challenges and Trends 6 1.4 Conclusion 9 2 Remote Patient Monitoring by Artificial Intelligence: Bringing a Paradigm Shift to Healthcare 17 2.1 Introduction 18 2.2 Attributes of SHM and IoMT 20 2.3 The IoTM and SHM Frameworks 20 2.4 Data Security in SHM 23 2.5 Remote Heart Rate Tracking 23 2.6 Sensor Enabled IoT-based Devices 24 2.7 Superior Medical Technology 24 2.8 Smart Health Monitoring 25 2.9 Service Coordination in Healthcare 25 2.10 Conclusion 26 3 Advancement in AI Enables Hospital Movement at Home 31 3.1 Introduction 31 3.2 ⁰́₋Health Smart Home⁰́₊ 33 3.3 HSH Applications 36 3.4 Driving Forces for Health Smart Homes 37 3.5 Advanced Technologies 39 3.6 Demonstration Space, Pilot Projects, and Full-Scale Housing 39 3.7 Design of a Smart Home Care System for Rural Elderly Based on AI 40 3.8 Conclusion 41 4 Obstacles and Complexity in AI Embedded Remote Health Monitoring 47 4.1 Introduction 48 4.2 Healthcare With AI 48 4.3 The Positive Effects of AI in Healthcare 49 4.4 Using AI to Improve Healthcare in Areas Such as Illness Prevention, Detection, and Treatment 50 4.5 Background Theory for AI and ML, with Instances in the Healthcare Industry 51 4.6 Improved Patient Care via Machine Learning and Increased Provider⁰́₃Patient Communication 52 4.7 Oncology, Big Data, and AI 52 4.8 Intelligent Digital Pathology with Deep Learning 53 4.9 Smart Health Data Analytics for Better Healthcare System Administration, Patient Outcomes, Scientific Discovery, and New Treatment Methods 53 4.10 Artificial Intelligence (AI) Applications in Orthopedics 53 4.11 Conclusion 56 5 Telehealth using Machine learning 65 5.1 Introduction 66 5.2 Related works 67 5.3 System of Watchful Waiting: A Proposed Scheme 69 5.4 Methodology 71 5.5 Hardware Information 74 5.6 Description of the Program 75 5.7 Conclusion 76 Index 81 |
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| illustrated | Not Illustrated |
| index_date | 2024-07-03T23:21:41Z |
| indexdate | 2024-07-10T10:09:06Z |
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| isbn | 9788770040242 8770040249 9781003810247 1003810241 9781032627991 1032627999 9781003810339 1003810330 |
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| physical | 1 Online-Ressource (xi, 82 Seiten) Illustrationen, Diagramme |
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| spelling | Malviya, Rishabha Verfasser aut Remote patient monitoring a computational perspective in healthcare Rishabha Malviya, Priyanshi Goyal Gistrup, Denmark River Publishers [2023] 1 Online-Ressource (xi, 82 Seiten) Illustrationen, Diagramme txt rdacontent c rdamedia cr rdacarrier River Publishers rapids series in biotechnology and medical research Preface ix About the Authors xi 1 Future of Remote Patient Monitoring with AI: An Overview 1 1.1 Introduction 1 1.2 Impact of AI on RPM 3 1.3 AI in RPM: Challenges and Trends 6 1.4 Conclusion 9 2 Remote Patient Monitoring by Artificial Intelligence: Bringing a Paradigm Shift to Healthcare 17 2.1 Introduction 18 2.2 Attributes of SHM and IoMT 20 2.3 The IoTM and SHM Frameworks 20 2.4 Data Security in SHM 23 2.5 Remote Heart Rate Tracking 23 2.6 Sensor Enabled IoT-based Devices 24 2.7 Superior Medical Technology 24 2.8 Smart Health Monitoring 25 2.9 Service Coordination in Healthcare 25 2.10 Conclusion 26 3 Advancement in AI Enables Hospital Movement at Home 31 3.1 Introduction 31 3.2 ⁰́₋Health Smart Home⁰́₊ 33 3.3 HSH Applications 36 3.4 Driving Forces for Health Smart Homes 37 3.5 Advanced Technologies 39 3.6 Demonstration Space, Pilot Projects, and Full-Scale Housing 39 3.7 Design of a Smart Home Care System for Rural Elderly Based on AI 40 3.8 Conclusion 41 4 Obstacles and Complexity in AI Embedded Remote Health Monitoring 47 4.1 Introduction 48 4.2 Healthcare With AI 48 4.3 The Positive Effects of AI in Healthcare 49 4.4 Using AI to Improve Healthcare in Areas Such as Illness Prevention, Detection, and Treatment 50 4.5 Background Theory for AI and ML, with Instances in the Healthcare Industry 51 4.6 Improved Patient Care via Machine Learning and Increased Provider⁰́₃Patient Communication 52 4.7 Oncology, Big Data, and AI 52 4.8 Intelligent Digital Pathology with Deep Learning 53 4.9 Smart Health Data Analytics for Better Healthcare System Administration, Patient Outcomes, Scientific Discovery, and New Treatment Methods 53 4.10 Artificial Intelligence (AI) Applications in Orthopedics 53 4.11 Conclusion 56 5 Telehealth using Machine learning 65 5.1 Introduction 66 5.2 Related works 67 5.3 System of Watchful Waiting: A Proposed Scheme 69 5.4 Methodology 71 5.5 Hardware Information 74 5.6 Description of the Program 75 5.7 Conclusion 76 Index 81 This book provides a multidisciplinary overview of the design and implementation of systems for remote patient monitoring and healthcare. Readers are guided through the components of such a system and shown how they could be integrated into a coherent framework for deployment in practice. The book ends with a discussion of case studies to provide practical examples and design methods for remote healthcare systems with different needs. This book contains information that will be helpful to undergraduate and postgraduate students, academic and professional researchers, and individuals who employ computational intelligence. By presenting new models of care and support, AI in medicine is having an impact on the entire value chain of clinical practice and the patient care delivery system. This is especially evident in telemedicine breakthroughs, where applications of AI are utilized to assist, complement, or create new forms of remote healthcare. Through the use of communications technology, telemedicine enables medical professionals to examine, diagnose, and treat patients remotely. Now, the technology might also integrate online diagnostics, etc., to increase the effectiveness of the healthcare system and enhance patient outcomes. By enabling elderly people to live independently, technological advancements in fields like remote patient monitoring (RPM) systems can revolutionize senior care. Medical diagnosis will improve, and remote patient monitoring will become simpler thanks to artificial intelligence. The resistance of many patients and doctors to using the telemedicine idea for medical visits will probably be overcome by AI automation Patient monitoring Telecommunication in medicine Artificial intelligence / Medical applications Monitoring, Physiologic Monitorage (Soins hospitaliers) Télémédecine Intelligence artificielle en médecine TECHNOLOGY / Telecommunications Goyal, Priyanshi Sonstige oth Print version 9781003810339 Erscheint auch als Druck-Ausgabe 978-87-7004-025-9 87-7004-025-7 https://ieeexplore.ieee.org/book/10217082 Aggregator URL des Erstveröffentlichers Volltext https://www.taylorfrancis.com/books/9781032627991 Taylor & Francis |
| spellingShingle | Malviya, Rishabha Remote patient monitoring a computational perspective in healthcare Preface ix About the Authors xi 1 Future of Remote Patient Monitoring with AI: An Overview 1 1.1 Introduction 1 1.2 Impact of AI on RPM 3 1.3 AI in RPM: Challenges and Trends 6 1.4 Conclusion 9 2 Remote Patient Monitoring by Artificial Intelligence: Bringing a Paradigm Shift to Healthcare 17 2.1 Introduction 18 2.2 Attributes of SHM and IoMT 20 2.3 The IoTM and SHM Frameworks 20 2.4 Data Security in SHM 23 2.5 Remote Heart Rate Tracking 23 2.6 Sensor Enabled IoT-based Devices 24 2.7 Superior Medical Technology 24 2.8 Smart Health Monitoring 25 2.9 Service Coordination in Healthcare 25 2.10 Conclusion 26 3 Advancement in AI Enables Hospital Movement at Home 31 3.1 Introduction 31 3.2 ⁰́₋Health Smart Home⁰́₊ 33 3.3 HSH Applications 36 3.4 Driving Forces for Health Smart Homes 37 3.5 Advanced Technologies 39 3.6 Demonstration Space, Pilot Projects, and Full-Scale Housing 39 3.7 Design of a Smart Home Care System for Rural Elderly Based on AI 40 3.8 Conclusion 41 4 Obstacles and Complexity in AI Embedded Remote Health Monitoring 47 4.1 Introduction 48 4.2 Healthcare With AI 48 4.3 The Positive Effects of AI in Healthcare 49 4.4 Using AI to Improve Healthcare in Areas Such as Illness Prevention, Detection, and Treatment 50 4.5 Background Theory for AI and ML, with Instances in the Healthcare Industry 51 4.6 Improved Patient Care via Machine Learning and Increased Provider⁰́₃Patient Communication 52 4.7 Oncology, Big Data, and AI 52 4.8 Intelligent Digital Pathology with Deep Learning 53 4.9 Smart Health Data Analytics for Better Healthcare System Administration, Patient Outcomes, Scientific Discovery, and New Treatment Methods 53 4.10 Artificial Intelligence (AI) Applications in Orthopedics 53 4.11 Conclusion 56 5 Telehealth using Machine learning 65 5.1 Introduction 66 5.2 Related works 67 5.3 System of Watchful Waiting: A Proposed Scheme 69 5.4 Methodology 71 5.5 Hardware Information 74 5.6 Description of the Program 75 5.7 Conclusion 76 Index 81 |
| title | Remote patient monitoring a computational perspective in healthcare |
| title_auth | Remote patient monitoring a computational perspective in healthcare |
| title_exact_search | Remote patient monitoring a computational perspective in healthcare |
| title_exact_search_txtP | Remote patient monitoring a computational perspective in healthcare |
| title_full | Remote patient monitoring a computational perspective in healthcare Rishabha Malviya, Priyanshi Goyal |
| title_fullStr | Remote patient monitoring a computational perspective in healthcare Rishabha Malviya, Priyanshi Goyal |
| title_full_unstemmed | Remote patient monitoring a computational perspective in healthcare Rishabha Malviya, Priyanshi Goyal |
| title_short | Remote patient monitoring |
| title_sort | remote patient monitoring a computational perspective in healthcare |
| title_sub | a computational perspective in healthcare |
| url | https://ieeexplore.ieee.org/book/10217082 https://www.taylorfrancis.com/books/9781032627991 |
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