Preface xvii

Part 1: Foundations of AI in Medical Imaging and Healthcare Systems 1

1 Deep Learning for Medical Imaging Analysis: Techniques, Challenges, and Applications 3
Amrita, Khalil Haruna Aminu, Mustapha Mukhtar Muhammad and Ibrahim Nayaya Isah

1.1 Introduction 4
1.2 Literature Review 5
1.3 Deep Learning 12
1.4 Medical Imaging 14
1.5 Role of Deep Learning in Medical Imaging 17
1.6 Key Contributions of DL in Medical Imaging 18
1.7 Conclusion 19

2 Secure and Intelligent Healthcare: Integrating Blockchain, Federated Learning, and Cognitive IoT 25
Adarsh Tiwari, Renu Mishra, Sneha Sinha, Mamta Narwaria and Anmol Kr. Sah

2.1 Introduction 26
2.2 Cognitive IoT in Healthcare: Foundation and Relevance 27
2.3 Blockchain for Secure Health Data Exchange 28
2.4 Proposed Framework for Blockchain-Enabled CIoT Healthcare 29
2.5 Security, Privacy, and Compliance Considerations 31
2.6 Challenges and Future Directions 34
2.7 Some Proposed Framework and Its Validation 36
2.8 Conclusion 39

3 Artificial Intelligence in Nonalcoholic Fatty Liver Disease: Enhancing Prediction, Diagnosis, and Treatment Outcomes 43
Tanisha Salhotra, Amit Kumar Singh, Vivek Kumar Garg and Aditya Kamboj

3.1 Introduction 44
3.2 Identifying the Patients at Risk of NAFLD 45
3.3 Diagnosis of NAFLD Severity 46
3.4 Utilizing AI for Early Identification and Risk Categorization 47
3.5 Digital Pathology: AI-Powered Analysis of Biopsy Samples 48
3.6 Predicting Disease Progression 49
3.7 AI-Driven Imaging Techniques for Diagnosing NAFLD 50
3.8 Using AI to Advance NAFLD Drug Discovery and Clinical Trials NAFLD 51
3.9 Conclusion 53

4 AI-Driven Early Disease Detection 57
K. Deepa, N. Sharmila Banu and G. Dhanraj

4.1 Introduction 57
4.2 Cognitive Impairment: Definitions, Prevalence, and Clinical Impact 59
4.3 Concept of Cognitive IoT 61
4.4 Data Flow in Cognitive IoT Systems for Cognitive Health Monitoring 62
4.5 AI Techniques in Cognitive IoT 64
4.6 Enabling Technologies (Compressed) 67
4.7 Digital Biomarkers and Data Analytics 68
4.8 Wearable Devices in Clinical Trials 69
4.9 Challenges and Limitations 71
4.10 Future Directions 72
4.11 Conclusion 72

Part 2: Advanced Predictive Modeling and Diagnostic Applications 75

5 Modeling of Smart Health Systems with Delay Differential Equations for Predictive Analytics 77
Pankaj Kumar, Pankaj Rai and Bimal Kumar Mishra

5.1 Introduction 78
5.2 Literature Review 78
5.3 Mathematical Model 80
5.4 Numerical Simulation and Validation 84
5.5 Discussion 88
5.6 Conclusion 89

6 Neurodegenerative Disorders: An Overview of Parkinson Disease, Alzheimer's Disease, Dementia and Other Conditions 93
Shreeya Arora, Namrata Dash and Kalpana Katiyar

6.1 Introduction 94
6.2 Pathobiology of Neurodegeneration 96
6.3 Parkinson's Disease (PD) 100
6.4 Alzheimer's Disease (AD) 104
6.5 Dementia and Related Conditions 108
6.6 Other Neurodegenerative Disorders 113
6.7 Diagnostics and Biomarker Development 116
6.8 Therapeutics and Translational Advances 119
6.9 Future Directions in Neurodegenerative Research 124
6.10 Conclusion 127

7 Deep Learning-Based Diagnostic System for Histopathological Detection of Uterine Cancer Subtypes 133
Subbulakshmi T. and Atharva Bandekar

7.1 Introduction 134
7.2 AI Advances in Histopathology: State of the Art and Gaps 135
7.3 Proposed AI Pathology Pipeline Building Method 138
7.4 Discussion: Implications and Future Directions 149

8 AI-Powered Smart Prosthetics and Neural Interfaces 155
Janu Chandak and Pery Patel

8.1 Introduction 156
8.2 Hardware Components 158
8.3 AI Algorithms for Neural Decoding 160
8.4 Sensory Restoration Via Haptic Feedback 161
8.5 Ethical and Privacy Considerations 163
8.6 Applications in Rehabilitation and Performance 165
8.7 Challenges and Future Directions 165

Part 3: Intelligent Systems and Human-Machine Integration 173

9 Neural and Muscular Feedback-Driven Adaptive Prosthetics 175
Janu Chandak and Pery Patel

9.1 Introduction 176
9.2 Physiological Signal Acquisition 183
9.3 Signal Processing and AI Integration 191
9.4 Actuator and Feedback Systems 194
9.5 Case Studies 197
9.6 Challenges and Limitations 199
9.7 Future Prospects in Adaptive Prosthetics 200

10 Decoding Brain Signals Using a Hybrid LSTM-CNN Deep Learning Model 209
Sankalp Chakre, Sarvesh Chaudhari, Nirdosh Chavhan, Adwait Gondhalekar and Riddhi Mirajkar

10.1 Introduction 210
10.2 Literature Survey 211
10.3 Proposed Methodology 215
10.4 Result 223
10.5 Conclusion 227
10.6 Future Scope 227

11 Multimodal GNN-Based Recommendation System for Children's Movies with Genre-Aware Evaluation and Visualization 231
Lucky Harichandan and Satyabrata Lenka

11.1 Introduction 232
11.2 Related Work 233
11.3 Dataset and Preprocessing 234
11.4 Results and Discussion 240
11.5 Conclusion 242

12 Market Adoption Strategies for Cognitive IoT in Smart Healthcare 245
Shrutika Mishra and Priyanshu Mishra

12.1 Introduction 246
12.2 Literature Review 249
12.3 Research Methodology 251
12.4 Limitations 255
12.5 Future Research Directions 258

Part 4: Data-Driven Healthcare Management and Cross-Domain Applications 261

13 Data-Driven Decision-Making in Healthcare Management Using Cognitive IoT: A Business and Management Perspective 263
Priyanshu Mishra and Shrutika Mishra

13.1 Introduction 264
13.2 Literature Review 266
13.3 Research Methodology 274
13.4 Future Directions 278
13.5 Conclusion 279

14 Predictive Analytics in Healthcare 283
Amrita, Kabiru Uba Kiru and Saeed Aliyu Usman

14.1 Introduction 284
14.2 Literature Review 285
14.3 Predictive Analytics 290
14.4 Healthcare 294
14.5 Roles of Predictive Analytics in Healthcare 294
14.6 Technologies Supporting Predictive Analytics in Healthcare 296
14.7 Challenges in Implementing Predictive Analytics in Healthcare 297
14.8 Conclusion 298

15 Effect of Packaging Material in the Supply Chain: A Case Study of Dairy Packaging 303
Saureng Kumar and Ankita Panwar

15.1 Introduction 304
15.2 Literature Review 306
15.3 Material and Method 307
15.4 Result 308
15.5 Conclusion 311

16 The Role of Machine Learning in Advancing Intelligent Conversational Systems 315
Sonu Rana, Ayantika Das, Shankar Prasad Mitra and Riya Sil

16.1 Introduction 316
16.2 Literature Review 318
16.3 Role of Machine Learning in Conversational AI Development 318
16.4 Training and Evaluation 323
16.5 Advanced Topics and Emerging Trends 327
16.6 Ethical Considerations 329
16.7 Conclusion 329

17 A Data-Driven Approach to Predicting Dengue Fever: Integrating Climate Data and Machine Learning 333
Eswar Reddy and Tannistha Pal

17.1 Introduction 334
17.2 Literature Review 335
17.3 Dataset and Features 337
17.4 Proposed Method 339
17.5 Results 343
17.6 Discussion 346
17.7 Conclusion 346

References 347
Index 349