Computational Intelligence in Healthcare
Applications, Challenges, and Management
Herausgeber: Gupta, Meenu; Kumar, Rakesh; Ahmed, Shakeel
Computational Intelligence in Healthcare
Applications, Challenges, and Management
Herausgeber: Gupta, Meenu; Kumar, Rakesh; Ahmed, Shakeel
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This book focuses on the fundamentals of computer intelligence and contains state-of-the-art methods of CI and other allied techniques used in the healthcare system, as well as advances in different CI methods that will confront the problem of effective data analysis and storage faced by healthcare institutions.
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This book focuses on the fundamentals of computer intelligence and contains state-of-the-art methods of CI and other allied techniques used in the healthcare system, as well as advances in different CI methods that will confront the problem of effective data analysis and storage faced by healthcare institutions.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 214
- Erscheinungstermin: 10. Februar 2023
- Englisch
- Abmessung: 234mm x 156mm x 14mm
- Gewicht: 499g
- ISBN-13: 9781032304939
- ISBN-10: 1032304936
- Artikelnr.: 66268679
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- 06621 890
- Verlag: Taylor & Francis Ltd (Sales)
- Seitenzahl: 214
- Erscheinungstermin: 10. Februar 2023
- Englisch
- Abmessung: 234mm x 156mm x 14mm
- Gewicht: 499g
- ISBN-13: 9781032304939
- ISBN-10: 1032304936
- Artikelnr.: 66268679
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- 06621 890
Dr. Meenu Gupta is an Associate Professor at the UIE-CSE Department, Chandigarh University, India. She has completed her PhD degree in Computer Science and Engineering with emphasis on Traffic Accident Severity Problems from Ansal University, Gurgaon, India, year 2020. She has more than 13 years of teaching experience. Her areas of research cover the fields of Machine Learning, Intelligent Systems, Data mining, with a specific interest in Artificial Intelligence, Smart Cities, etc. She has edited two books on Healthcare and Cancer diseases and authored four engineering books. She works as a reviewer for several journals including Soft Computing, Big Data, Scientific Report, and etc. She is a life member of ISTE and IAENG. She has authored or co-authored more than 20 book chapters and over 60 papers in refereed international journals and conferences. She has filled 3 Indian patents and awarded with best faculty and researcher of the department in year 2021. Dr. Shakeel Ahmed is Associate Professor at the College of Computer Sciences and Information Technology, King Faisal University, Saudi Arabia. His areas of interest include Software Verification and Validation, Mobile AdHoc Networks, Software Engineering, and Cloud Computing. He is the head of the cloud computing research group at the College of Computer Sciences and Information technology, KFU. He has authored several research papers in indexed and impact factor research journals and IEEE international conferences. He is a PC member for several international conferences and an active reviewer for quartile journals. He holds a Ph.D. degree in Computer Science from Indore University, India. Dr. Rakesh Kumar is a Professor in the Department of Computer Science Engineering at Chandigarh University, Punjab, India. He has done his Ph.D. in Computer Science and Engineering from Punjab Technical University, Jalandhar, year 2017. He has more than 17 years of teaching experience. His research interests are IoT, Machine Learning and Natural Language Processing. He has published many authored books with reputed publisher. He works as a reviewer for several journals including Big Data, CMC, Scientific Report and TSP. He has authored or co-authored more than 50 publications various National, International Conferences and International Journals. He is also working as a PI in AIMS funding project with collaboration of Chandigarh University, Punjab. Chadi Altrjman is working as an associate scientist and researcher in Near East University, Cyprus and received his Bachelor of Engineering from the University of Waterloo, Ontario, Canada. And now, he is involved in several smart projects via which he is expanding his practical skills. His research interests include AI and machine learning, Wireless Sensor Networks, Chemical Sensors, Sustainable & Renewable Energy Integration, Distributed Power Generation, and Smart Grid Applications.
1. Introduction to Computational Intelligence in Healthcare: Applications,
Challenges, and Management, 2. Role of IoT and Machine Learning for
E-Healthcare Management, 3. Telemedical and Remote Healthcare Monitoring
Using IoT and Machine Learning, 4. Efficient Ways for Healthcare Data
Management Using Data Science and Machine Learning, 5. A Novel Scheme to
Manage the E-Healthcare System Using Cloud Computing and the Internet of
Things, 6. Automating Remote Point-of-Care ECG Diagnostics via
Decentralized Report Routing Algorithm, 7. Evaluation of Deep Image
Embedders for Healthcare Informatics Improvement Using Visualized
Performance Metrics, 8. A Comparative Analysis for Analysing the
Performance of Convolutional Neural Network versus Other Machine Learning
Techniques to Assess Cardiovascular Disease, 9. A Study of Machine Learning
Initiatives in the Global Healthcare Sector Using Different Case Studies,
10. Autism Spectrum Disorder Diagnostic System Using Adaptive Neuro Fuzzy
Inference System, 11. Detection of Diabetic Foot Ulcer (DFU) With AlexNet
and ResNet-101, 12. A Case Study-Based Analysis on Remote Medical
Monitoring with AWS Cloud and Internet of Things (IoT)
Challenges, and Management, 2. Role of IoT and Machine Learning for
E-Healthcare Management, 3. Telemedical and Remote Healthcare Monitoring
Using IoT and Machine Learning, 4. Efficient Ways for Healthcare Data
Management Using Data Science and Machine Learning, 5. A Novel Scheme to
Manage the E-Healthcare System Using Cloud Computing and the Internet of
Things, 6. Automating Remote Point-of-Care ECG Diagnostics via
Decentralized Report Routing Algorithm, 7. Evaluation of Deep Image
Embedders for Healthcare Informatics Improvement Using Visualized
Performance Metrics, 8. A Comparative Analysis for Analysing the
Performance of Convolutional Neural Network versus Other Machine Learning
Techniques to Assess Cardiovascular Disease, 9. A Study of Machine Learning
Initiatives in the Global Healthcare Sector Using Different Case Studies,
10. Autism Spectrum Disorder Diagnostic System Using Adaptive Neuro Fuzzy
Inference System, 11. Detection of Diabetic Foot Ulcer (DFU) With AlexNet
and ResNet-101, 12. A Case Study-Based Analysis on Remote Medical
Monitoring with AWS Cloud and Internet of Things (IoT)
1. Introduction to Computational Intelligence in Healthcare: Applications,
Challenges, and Management, 2. Role of IoT and Machine Learning for
E-Healthcare Management, 3. Telemedical and Remote Healthcare Monitoring
Using IoT and Machine Learning, 4. Efficient Ways for Healthcare Data
Management Using Data Science and Machine Learning, 5. A Novel Scheme to
Manage the E-Healthcare System Using Cloud Computing and the Internet of
Things, 6. Automating Remote Point-of-Care ECG Diagnostics via
Decentralized Report Routing Algorithm, 7. Evaluation of Deep Image
Embedders for Healthcare Informatics Improvement Using Visualized
Performance Metrics, 8. A Comparative Analysis for Analysing the
Performance of Convolutional Neural Network versus Other Machine Learning
Techniques to Assess Cardiovascular Disease, 9. A Study of Machine Learning
Initiatives in the Global Healthcare Sector Using Different Case Studies,
10. Autism Spectrum Disorder Diagnostic System Using Adaptive Neuro Fuzzy
Inference System, 11. Detection of Diabetic Foot Ulcer (DFU) With AlexNet
and ResNet-101, 12. A Case Study-Based Analysis on Remote Medical
Monitoring with AWS Cloud and Internet of Things (IoT)
Challenges, and Management, 2. Role of IoT and Machine Learning for
E-Healthcare Management, 3. Telemedical and Remote Healthcare Monitoring
Using IoT and Machine Learning, 4. Efficient Ways for Healthcare Data
Management Using Data Science and Machine Learning, 5. A Novel Scheme to
Manage the E-Healthcare System Using Cloud Computing and the Internet of
Things, 6. Automating Remote Point-of-Care ECG Diagnostics via
Decentralized Report Routing Algorithm, 7. Evaluation of Deep Image
Embedders for Healthcare Informatics Improvement Using Visualized
Performance Metrics, 8. A Comparative Analysis for Analysing the
Performance of Convolutional Neural Network versus Other Machine Learning
Techniques to Assess Cardiovascular Disease, 9. A Study of Machine Learning
Initiatives in the Global Healthcare Sector Using Different Case Studies,
10. Autism Spectrum Disorder Diagnostic System Using Adaptive Neuro Fuzzy
Inference System, 11. Detection of Diabetic Foot Ulcer (DFU) With AlexNet
and ResNet-101, 12. A Case Study-Based Analysis on Remote Medical
Monitoring with AWS Cloud and Internet of Things (IoT)