Schweitzer Fachinformationen
Wenn es um professionelles Wissen geht, ist Schweitzer Fachinformationen wegweisend. Kunden aus Recht und Beratung sowie Unternehmen, öffentliche Verwaltungen und Bibliotheken erhalten komplette Lösungen zum Beschaffen, Verwalten und Nutzen von digitalen und gedruckten Medien.
The book provides an essential overview of AI techniques in disease management and how these computational methods can lead to further innovations in healthcare.
Design and Forecasting Models for Disease Management is a resourceful volume of 13 chapters that elaborates on computational methods and how AI techniques can aid in smart disease management. It contains several statistical and AI techniques that can be used to acquire data on many different diseases. The main objective of this book is to demonstrate how AI techniques work for early disease detection and forecasting useful information for medical experts. As such, this volume intends to serve as a resource to elicit and elaborate on possible intelligent mechanisms for helping detect early signs of diseases. Additionally, the book examines numerous machine learning and data analysis techniques in the biomedical field that are used for detecting and forecasting disease management at the cellular level. It discusses various applications of image segmentation, data analysis techniques, and hybrid machine learning techniques for illnesses, and encompasses modeling, prediction, and diagnosis of disease data.
Audience
Researchers, engineers and graduate students in the fields of computational biology, information technology, bioinformatics, and epidemiology.
Pijush Dutta, PhD, is an assistant professor and head of the Department of Electronics and Communication Engineering at Greater Kolkata College of Engineering and Management, West Bengal, India, with over 11 years of teaching and over seven years of research experience. He has published eight books, as well as 14 patents and over 100 research articles in national and international journals and conferences. His research interests include sensors and transducers, nonlinear process control systems, the Internet of Things (IoT), and machine and deep learning.
Sudip Mandal, PhD, is an assistant professor in the Electronics and Communication Engineering Department at Jalpaiguri Government Engineering College, India. He has over 50 publications in national and international peer-reviewed journals and conferences, as well as two Indian patents and two books. He is a member of the Institute of Electrical and Electronics Engineers' Computational Intelligence Society.
Korhan Cengiz, PhD, is an associate professor in the Department of Computer Engineering at Istinye University, Istanbul, Turkey. He has published over 40 articles in international peer-reviewed journals, five international patents, and edited over ten books. His research interests include wireless sensor networks, wireless communications, and statistical signal processing.
Arindam Sadhu, PhD, is an assistant professor in the Electronics and Communication Engineering Department at Swami Vivekananda University, West Bengal, India, with over five years of teaching and over three years of research experience. He has published two international patents and over ten articles in national and international journals and conferences. His research interests include post-complementary metal-oxide-semiconductor transistors, quantum computing, and quantum dot cellular automata.
Gour Gopal Jana is an assistant professor in the Electronics and Communication Engineering Department at Greater Kolkata College of Engineering and Management, West Bengal, India, with over 13 years of teaching and over three years of research experience. He has published two international patents and over ten research articles in national and international journals and conference proceedings. His research interests include metal thin film sensors, biosensors, nanobiosensors, and nanocomposites.
Preface xvii
Part 1: Safety and Regulatory Aspects for Disease Pre-Screening 1
1 A Study of Possible AI Aversion in Healthcare Consumers 3Tanupriya Mukherjee and Anusriya Mukherjee
1.1 Introduction to AI in Healthcare 4
1.2 Consumer Reluctance to Utilize AI in Healthcare: Present Scenario 8
1.3 Economic Implications of AI Aversion 17
1.4 Overcoming Resistance to Medical AI 22
1.5 Ethical Considerations and Governance 26
1.6 Future Outlook and Opportunities 31
1.7 Conclusion 37
2 A Study of AI Application Through Integrated and Systematic Moral Cognitive Therapy in the Healthcare Sector 47Anusriya Mukherjee, Tanupriya Mukherjee and Mili Mitra Roy
2.1 Introduction 48
2.2 What is Integrated and Systematic Moral Cognitive Therapy (ISMCT)? 54
2.3 The Role of AI in Healthcare: A Fine Balance Between Ethics and Innovation 61
2.4 Advancing Research in AI-Integrated Moral Cognitive Therapy 67
2.5 Conclusion 70
3 A Strategic Model to Control Non-Communicable Diseases 77Soumik Gangopadhyay, Amitava Ukil, Soma Sur and Saugat Ghosh
3.1 Introduction 78
3.2 Survey of Literature 84
3.3 Proposed Model 87
3.4 Conclusion 91
4 Image Compression Technique Using Color Filter Array (CFA) for Disease Diagnosis and Treatment 99Indrani Dalui, Avisek Chatterjee, Surajit Goon and Pubali Das Sarkar
4.1 Introduction 100
4.2 Related Works 102
4.3 Proposed Model 108
4.4 Implementation 110
4.5 Results 111
4.6 Conclusion 112
5 Research in Image Processing for Medical Applications Using the Secure Smart Healthcare Technique 115Debraj Modak and Chowdhury Jaminur Rahaman
5.1 Introduction 116
5.2 Classification of Digital Images 121
5.3 Methods 130
5.4 Segmentation and Database Extraction with Neural Networks 133
5.5 Applications in Medical Image Analysis 135
5.6 Standardize Analytics Pipeline for the Health Sector 136
5.7 Feature Extraction/Selection 138
5.8 Image-Based Forecasting Using Internet of Things (IoT) in Smart Healthcare System 141
5.9 IoT Monitoring Applications Based on Image Processing 143
5.10 Significance of Computer-aided Big Healthcare Data (BHD) for Medical Image Processing 145
5.11 Applications of Big Data 147
5.12 Conclusion 150
6 Comparative Study on Image Enhancement Techniques for Biomedical Images 155Sudip Mandal, Uma Biswas, Aparna Mahato and Aurgha Karmakar
6.1 Introduction 156
6.2 Literature Review 157
6.3 Theoretical Concepts 158
6.4 Results and Discussion 166
6.5 Conclusion 178
7 Exploring Parkinson's Disease Progression and Patient Variability: Insights from Clinical and Molecular Data Analysis 181Amit Kumar, Neha Sharma and Korhan Cengiz
7.1 Introduction 182
7.2 Literature Review 183
7.3 Data Review 184
7.4 Parkinson's Dynamic for Patients in Train 196
7.5 Conclusion 197
8 A Survey-Based Comparative Study on Machine Learning Techniques for Early Detection of Mental Illness 201Prachi Majumder, Sompadma Mukherjee, Shreyashi Saha, Tamasree Biswas, Mousumi Saha, Deepanwita Das and Suchismita Maiti
8.1 Introduction 201
8.2 Background 202
8.3 Review of Previous Works 203
8.4 Comparative Result 208
8.5 Discussion 212
8.6 Conclusion 213
Part 2: Clinical Decision Support System for Early Disease Detection and Management 215
9 Diagnostics and Classification of Alzheimer's Diseases Using Improved Deep Learning Architectures 217Mainak Dey, Pijush Dutta and Gour Gopal Jana
9.1 Introduction 218
9.2 Related Works 219
9.3 Method 222
9.4 Result Analysis 225
9.5 Conclusion 232
10 Perform a Comparative Study Based on Conventional Machine Learning Approaches for Human Stress Level Detection 237Pratham Sharma, Prerana Singh, Mahe Parah, Shyamapriya Chatterjee, Anirban Bhar, Soumya Bhattacharyya and Pijush Dutta
10.1 Introduction 238
10.2 Related Work 239
10.3 Architecture Design 242
10.4 Experiment 244
10.5 Result Analysis 246
10.6 Conclusion 248
11 Diabetes Prediction Using a Hybrid PCA-Based Feature Selection and Computational Machine Learning Algorithm 253Sumanta Dey, Pijush Dutta, Gour Gopal Jana and Arindam Sadhu
11.1 Introduction 254
11.2 Related Work 254
11.3 Proposed Workflow 256
11.4 Result Analysis 261
11.5 Conclusion and Future Work 265
12 A Robust IoT-Based Approach to Enhance Cybersecurity and Patient Trust in the Smart Health Care System: Zero-Trust Model 269Raghunath Maji, Biswajit Gayen and Sandeepan Saha
12.1 Introduction 270
12.2 Security Threats on Smart Healthcare 271
12.3 Smart Healthcare Security and Four-Dimension Model 273
12.4 Conclusion and Future Prospects 279
13 Safeguarding Digital Health: A Novel Approach to Malicious Device Detection in Smart Healthcare 283Raghunath Maji and Biswajit Gayen
13.1 Introduction 284
13.2 Related Work 286
13.3 Our Proposed Framework 289
13.4 Overview of Our Proposed Framework 289
13.5 Evaluation Procedure 291
13.6 Performance Evaluation 292
13.7 Conclusion 293
References 294
Index 297
Dateiformat: PDFKopierschutz: Adobe-DRM (Digital Rights Management)
Systemvoraussetzungen:
Das Dateiformat PDF zeigt auf jeder Hardware eine Buchseite stets identisch an. Daher ist eine PDF auch für ein komplexes Layout geeignet, wie es bei Lehr- und Fachbüchern verwendet wird (Bilder, Tabellen, Spalten, Fußnoten). Bei kleinen Displays von E-Readern oder Smartphones sind PDF leider eher nervig, weil zu viel Scrollen notwendig ist. Mit Adobe-DRM wird hier ein „harter” Kopierschutz verwendet. Wenn die notwendigen Voraussetzungen nicht vorliegen, können Sie das E-Book leider nicht öffnen. Daher müssen Sie bereits vor dem Download Ihre Lese-Hardware vorbereiten.
Bitte beachten Sie: Wir empfehlen Ihnen unbedingt nach Installation der Lese-Software diese mit Ihrer persönlichen Adobe-ID zu autorisieren!
Weitere Informationen finden Sie in unserer E-Book Hilfe.
