KI-Beratung Beta

Gutscheinbedingungen

**Gültig bis 03.11.2026 auf fremdsprachige Bücher online auf thalia.at und in der Thalia App. Einzelne Artikel können ausgeschlossen sein. Ausgenommen sind preisgebundene Artikel & eBooks. Pro Einkauf einmal einlösbar. Click & Collect nur bei Onlinevorabzahlung möglich. Keine Barauszahlung. Nicht kombinierbar mit anderen Aktionen und Gutscheinen. Gutschein wird auf max. 500€ Bestellwert angerechnet. Nicht gültig für Geschenkkarten, Versandkosten und Services.

Produktbild: Data-Driven Sports Medicine
Vorbesteller Neu

Data-Driven Sports Medicine

259,99 €

inkl. gesetzl. MwSt., Versandkostenfrei


Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

09.11.2026

Herausgeber

Abhishek Kumar + weitere

Verlag

WILEY

Seitenzahl

640

Sprache

Englisch

ISBN

978-1-394-48644-1

Beschreibung

Portrait

Abhishek Kumar, PhD, is an Assistant Director and Associate Professor in the Computer Science and Engineering Department at Chandigarh University, Punjab, India. He has authored seven books, edited 51 books, and published more than 170 publications in reputed, peer-reviewed national and international journals, books, and conferences. His research areas include artificial intelligence, renewable energy, image processing, computer vision, data mining, and machine learning.

Pramod Singh Rathore, PhD, is an Assistant Professor in the Department of Computer and Communication Engineering at Manipal University Jaipur. With more than 12 years of academic teaching experience, he has published more than 85 papers in reputable, peer-reviewed national and international journals, books, and conferences. His research interests include NS2, computer networks, and mining.

Inam Ul Haq is an Assistant Professor in the School of Engineering and Technology at CGC University, Mohali, India. He has published 51 research articles and has actively participated in academic and research activities. His research interests include artificial intelligence, machine learning, deep learning, large language models, renewable energy, wind energy, and bioinspired algorithms.

Pooja Dixit is an Assistant Professor in the Department of Computer Science at Shri Ratanlal Kanwarlal Patni Girls' College, Kishangarh, India. With more than ten years of academic teaching and two years of research experience, she has published more than 30 research papers in reputed journals, books, and conferences. Her research interests include artificial intelligence, machine learning, and data mining.

Sachin Ahuja, PhD, is a Professor and Executive Director of UIE at Chandigarh University. He has led multiple funded research projects in artificial intelligence, machine learning, and data mining and has contributed to numerous academic books. He has also served as a guest editor for special issues in reputed international journals.

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

09.11.2026

Herausgeber

Verlag

WILEY

Seitenzahl

640

Sprache

Englisch

ISBN

978-1-394-48644-1

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

Noch keine Bewertungen vorhanden

Verfassen Sie die erste Bewertung zu diesem Artikel

Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.

Kundinnen und Kunden meinen

Bewertungen (0)

Die Leseprobe wird geladen.
  • Produktbild: Data-Driven Sports Medicine
  • Preface xxxv

    1 Deep Learning Fundamentals for Sports Science: Data-Driven Models for Performance and Injury Prevention 1
    Gitanjali Gupta and Inderdeep Kaur

    1.1 Introduction to Deep Learning in Sports Science 2
    1.2 Sports Science Data: Types, Sources, and Challenges 3

    2 Computer Vision in Sports Medicine 37
    Lokeshwer Sharma, Ravi Sandal, Ishan Thakur and Harish Sharma

    3 Computer Vision and Deep Learning for Intelligent Sports Injury Monitoring: From Theory to Practice 57
    Manju Lata Joshi, Megha Nain and Pratish Rawat

    3.1 Introduction 58
    3.2 Related Work 59
    3.3 Background on Biomechanical Injury Factors and Vision Sensors 61
    3.4 Deep Learning Framework for Vision-Based Injury 63
    3.5 Experiments 66
    3.6 Discussion 70
    3.7 Future Work 73
    3.8 Conclusion 75

    4 Trusted AI Models for Sports Injury Detection - Interpretable, Secure, and Ethical Deep Learning Frameworks 81
    Puja Srivastava, Inderdeep Kaur and Arti Shrivastava

    4.1 Introduction 82
    4.2 Sports Injury Detection: Challenges and Opportunities 83
    4.3 Deep Learning for Sports Injury Detection 86
    4.4 Trusted AI: Core Principles 89
    4.5 Explainable AI Frameworks for Clinical Trust 95
    4.6 Blockchain-Enabled Secure AI Systems 96
    4.7 Ethical, Legal, and Regulatory Considerations 98
    4.8 Future Directions and Research Challenges 101
    4.9 Conclusion 101

    5 Explainable and Trustworthy Deep Learning for Sports Injury Risk Assessment: A Blockchain-Enabled Framework 105
    Mamta

    5.1 Introduction 106
    5.2 Literature Review and Research Gap Analysis 109
    5.3 Sports Injury Risk Assessment: Data Characteristics and Challenges 113
    5.4 Deep Learning-Based Risk Prediction in Sports Injuries 115
    5.5 Explainable Artificial Intelligence for Sports Medicine Applications 117
    5.6 Blockchain-Enabled Trust Mechanisms for Sports Health Analytics 119
    5.7 Proposed Conceptual Framework for Explainable and Trustworthy Deep Learning 121
    5.8 Application Scenarios and Practical Use-Case Illustrations 124
    5.9 Ethical, Privacy, and Regulatory Concerns 126
    5.10 Open Challenges, Limitations, Future Research 128
    5.11 Conclusion 130

    6 Artificial Intelligence for Athlete Performance Monitoring: Data-Driven Models for Optimization, Injury Prevention and Decision Support 137
    Rajeshwari Pradhan and Inderdeep Kaur

    6.1 Introduction 138
    6.2 Data Sources for AI-Based Athlete Monitoring 139
    6.3 AI and Machine Learning Techniques in Performance Monitoring 142
    6.4 AI for Workload Optimization and Fatigue Detection 146
    6.5 Injury Risk Prediction Using AI 148
    6.6 Real-Time Analytics and Decision Support Systems 151
    6.7 Athlete Profiling and Personalization 154
    6.8 Ethical, Legal, and Reliability Considerations 156
    6.9 Challenges and Future Directions 158
    6.10 Conclusion 161

    7 Personalized Training and Rehabilitation Plans Using AI in Sports Medicine 167
    Sohom Saha, Mahendra Kumar Singh and Simran Obhrai

    7.1 Introduction 168
    7.2 Theoretical Foundation and AI Architecture 169
    7.3 Multimodal Data Integration and Sensor Technologies 173
    7.4 Injury Prediction and Prevention 177
    7.5 Personalized Rehabilitation Protocols 179
    7.6 Implementation Framework and Clinical Integration 182
    7.7 Case Studies and Applications 184
    7.8 Challenges and Limitations 185
    7.9 Future Directions and Emerging Technologies 187
    7.10 Conclusion 189

    8 Blockchain Technology in Healthcare and Sports Medicine: Enhancing Data Security, Transparency, and Performance Analytics 195
    Aditya Randev, Inderdeep Kaur and Aakriti Khanna

    8.1 Introduction 196
    8.2 Principles of Blockchain Technology 199
    8.3 Blockchain in Healthcare Systems 203
    8.4 Applications of Blockchain in Sports Medicine 208
    8.5 Blockchain-Enabled Telemedicine and Remote Monitoring 211
    8.6 Challenges and Limitations 214
    8.7 Future Trends and Research Directions 217
    8.8 Conclusion 220

    9 Blockchain Technology in Healthcare and Sports Medicine 225
    Seema Kharod, Jasneet Chawla and Hema Shekhawat

    9.1 Introduction 226
    9.2 Fundamentals of Blockchain Technology 227
    9.3 Challenges in Health and Sports Data Systems: A Blockchain-Based Solution 229
    9.4 Blockchain, IoT, and Wearables in Sports Medicine 235
    9.5 Case Studies and Real-World Implementations 237
    9.6 Future Trends in Blockchain for Health and Sports 240
    9.7 Conclusion 242

    10 Blockchain for Secure Athlete Health Records 245
    Biswajit Das, Himanshu Pabbi, Shweta Singh, Monika Mehra, Ruchika, Ishakshi Gupta and Subhash Chandra

    10.1 Introduction 246
    10.2 Athlete Health Records and Security Challenges 247
    10.3 Blockchain Fundamentals for Health Data Security 249
    10.4 Proposed Blockchain-Based Athlete Health Record Framework 249
    10.5 Machine Learning-Based Activity Classification 252
    10.6 Experimental Results and Analysis 255
    10.7 Security and Privacy Evaluation 257
    10.8 Challenges and Limitations 259
    10.9 Future Research Directions 259
    10.10 Conclusion 260

    11 Blockchain for Trust, Security and Data Management Smart Contracts in Sports Medicine 263
    Aafrina Aarfa, Nahid Khan, Huma, Ifra Aman and Shaima Saifi

    11.1 Introduction 264
    11.2 Problems with Traditional Centralized Systems 264
    11.3 Blockchain Technology 265
    11.4 Blockchain-Secured Patient Digital Twins: A Next-Generation Framework for Personalized Sports Medicine 269
    11.5 Blockchain-Enabled Sports Health Monitoring Systems: Improving Data Security and Privacy 274
    11.6 Concept of Smart Contracts 277
    11.7 Applications of Smart Contracts in Sports Medicine 279
    11.8 Smart Contracts for Athlete Data Privacy and Consent 282
    11.9 Smart Contract-Enabled Encrypted Role-Based Access Control for Healthcare 286
    11.10 Practical Model of Blockchain-Based Digital Transactions in Sports Ecosystems 288
    11.11 Ethical, Legal, and Regulatory Considerations 288
    11.12 Limitation and Challenges 289
    11.13 Future Scope and Research Directions 289

    12 Blockchain and IoT Integration in Wearable Sports Devices for Secure and Intelligent Sports Medicine 295
    Shubham Kumar, Inderdeep Kaur and Aakriti Khanna

    12.1 Introduction to Wearable Sports Devices 296
    12.2 IoT Use in Sports Medicine and Athlete Monitoring 297
    12.3 Data Security and Privacy Challenges 299
    12.4 Blockchain Fundamentals for Healthcare 302
    12.5 Blockchain-IoT Architecture 303
    12.6 Smart Contracts for Secure Data Sharing 305
    12.7 Applications in Performance Analysis 309
    12.8 Case Studies and Implementations 312
    12.9 Challenges and Limitations 315
    12.10 Ethical Considerations 317
    12.11 Future Trends and Directions 319
    12.12 Conclusion 320

    13 Artificial Intelligence-Enabled Doping Detection and Prevention in Sports Using Blockchain Technology 325
    Khalid Hafiz Mir and Anzah Bashir

    13.1 Introduction 326
    13.2 Doping Detection: Background and Limitations 327
    13.3 Artificial Intelligence for Doping Detection 328
    13.4 Blockchain for Integrity and Transparency 329
    13.5 Integrated AI-Blockchain Framework 330
    13.6 Operational Workflow 331
    13.7 Privacy and Ethical Considerations 332
    13.8 Applications and Benefits 332
    13.9 Challenges and Limitations 334
    13.10 Future Research Directions 334
    13.11 Conclusion 335

    14 Artificial Intelligence and Blockchain for Anti-Doping Control and Ethical Compliance in Sports Medicine 339
    Anzah Bashir and Khalid Hafiz Mir

    14.1 Introduction 340
    14.2 Background and Motivation 341
    14.3 Role of Artificial Intelligence in Anti-Doping and Ethics Monitoring 341
    14.4 Role of Blockchain in Integrity and Transparency 342
    14.5 Integrated AI-Blockchain Framework 342
    14.6 Operational Workflow 344
    14.7 Privacy and Ethical Considerations 345
    14.8 Applications and Benefits 346
    14.9 Challenges and Limitations 346
    14.10 Future Research Directions 347
    14.11 Conclusion 348

    15 Deep Learning Insights with Blockchain Trust Using Conversational AI on Sports Medicine 351
    Amanpreet Kaur and Neha Sharma

    15.1 Introduction 352
    15.2 Conversational AI Growth 354
    15.3 Issues with Conversational AI 362
    15.4 Ethical Considerations for Conversational AI 363
    15.5 Challenges 363
    15.6 Case Studies 364
    15.7 Future Directions 365
    15.8 Conclusion 367

    16 AI-Powered Detection and Prevention of Doping in Sports: A Blockchain-Driven Approach to Integrity and Fairness 371
    Abdul Malik Ansari

    16.1 Introduction 372
    16.2 Doping in Sports: Landscape, Challenges, and Threat Models 375
    16.3 AI-Based Doping Detection: Foundations and Model Design 378
    16.4 Blockchain for Anti-Doping Integrity: Secure Data Governance 381
    16.5 Proposed Unified Framework: AI and Blockchain Architecture 383
    16.6 Case Study/Simulation Design for Validation 386
    16.7 Ethical, Legal, and Regulatory Considerations 387
    16.8 Implementation Challenges and Future Research Directions 389
    16.9 Conclusion 390

    17 Case Studies in Data-Driven Sports Medicine 395
    Anuj Tiwari

    17.1 Introduction 396
    17.2 Framework for Data-Driven Sports Medicine Systems 396
    17.3 Case-Studies Design and Interpretation Approach 399
    17.4 Case Studies 400
    17.5 Cross-Case Synthesis and Emerging Patterns 414
    17.6 Ethical, Operational, and Trust 418
    17.7 Future Directions 419

    18 Artificial Intelligence-Based Personalized Training and Rehabilitation Planning: Application in Sports Medicine 423
    Jasia Farzeen, Huma Khan, Prachi Tiwari, Ifra Aman and Nahid Khan

    19 Computer Vision and Deep Learning for Personalized Rehabilitation and Injury Prevention in Sports Medicine 441
    Huma Khan, Jasia Farzeen, Sahar Zaidi, Ifra Aman and Nahid Khan

    19.1 Introduction 442
    19.2 Background and Conceptual Foundations 443
    19.3 Methodological Framework of Computer Vision Systems 446
    19.4 Computer Vision Use in Sports Medicine 450
    19.5 Injury Prediction and Preventive Decision-Making 452
    19.6 Challenges, Limitations, and Ethical Considerations 455
    19.7 The Future of AI-Driven Sports Medicine 456
    19.8 Discussion 456
    19.9 Conclusion 458

    20 Data-Driven Sports Medicine and Athlete Care: AI, Blockchain, and Explainable Deep Learning for Secure Performance Analytics and Anti-Doping Applications 461
    Bhaskar Marapelli, G. Shivakanth, Peddini Suresh Kumar, Maddhigalla Lakshumaiah and K. Aruna Bhaskar

    20.1 Introduction to Data-Driven Sports Medicine 462
    20.2 Sports Data Ecosystem and Digital Health Infrastructure 464
    20.3 Artificial Intelligence in Sports Medicine and Performance Analytics 466
    20.4 Explainable Deep Learning to Care about Athletes 468
    20.5 Blockchain Technology of Secure Sports Data Management 470
    20.6 Artificial Intelligence-Blockchain Hybrid Sports Medicine 472
    20.7 Artificial Intelligence and Secure Analytics in Anti-Doping 473
    20.8 Regulatory, Ethical, and Other Legal Cases 475
    20.9 Real-Life and Case Studies 476
    20.10 Challenges and Limitations 477

    21 Artificial Intelligence and Blockchain in Sports Medicine: Data-Driven, Secure, and Explainable Approaches for Performance, Injury Prevention, and Ethical Compliance 481
    Bhaskar Marapelli, G. Shivakanth, Kankatala Mayuri, Bechoo Lal and K. S. Ranadheer Kumar

    21.1 Introduction 482
    21.2 The Digital Health Infrastructure and Sports Data Ecosystem 484
    21.3 The Use of Artificial Intelligence in Sports Medicine and Athlete Performance 486
    21.4 Sports Medicine Explainable Artificial Intelligence 487
    21.5 Secure Sports Medicine Data Management Using Blockchain Technology 490
    21.6 Artificial Intelligence-Blockchain Comprehensive Athlete Care 491
    21.7 Applications of AI and Secure Analytics on Anti-Doping 492
    21.8 Legal, Regulatory, and Ethical 495
    21.9 Case Studies and Practical Applications 496
    21.10 Future Directions and New Trends 497

    22 Intelligent Sports Medicine Analytics: AI, Explainable Learning, and Blockchain for Secure and Predictive Athlete Care 501
    Shabeena Khan, P. Dharmendhra Kumar, Pampana Murali and Shweta Solanki

    22.1 Introduction 502
    22.2 Sports Medicine Data Ecosystem 504
    22.3 The Artificial Intelligence of Athlete Health and Performance 506
    22.4 Elucidable Learning Models in Sports Medicine 507
    22.5 Blockchain Secure Sports Medicine Analytics 510
    22.6 AI and Blockchain Frameworks 512
    22.7 Integrity Assurance and Anti-Doping Applications 513
    22.8 Ethical, Legal, and Governance Accounts 515
    22.9 Case Studies and Applications 517

    23 Game-Theoretic Data-Driven Sports Medicine: Deep Learning and Blockchain-Enabled Trust 521
    Kanika Singh, Aaryan Gupta, Kasvi Rajwar, Preeti Narooka and Sachi Singh

    23.1 Introduction 522
    23.2 Holistic View and Impact of Artificial Intelligence and Deep Learning in Smart Healthcare Systems 523
    23.3 Uses of AR and VR in AI, Robotics, and Medical Procedures 531
    23.4 AI for Athlete Performance Monitoring 532
    23.5 Implications of AI and Deep Learning in Smart Healthcare Systems 536
    23.6 Challenges in Implementing AI and Deep Learning in Smart Healthcare Systems 538
    23.7 Future Directions of AI and Deep Learning in Smart Healthcare Systems 540
    23.8 Conclusion 541

    24 Future Horizons of Data-Driven Sports Medicine: Convergence of Deep Learning, Blockchain, Digital Twins, and Personalized Athlete Care 545
    Dharmendra Dubey, Shweta Solanki, Shaloo Dadheech and Monika Tiwari

    24.1 Introduction 546
    24.2 Underpinnings of Data-Driven Sports Medicine 549
    24.3 Athlete Health and Performance Deep Learning 552
    24.4 Wearable Technologies and Edge AI 554
    24.5 Incredible Blockchain in Trustworthy Sports Healthcare 557
    24.6 Deep Learning and Blockchain Integration 559
    24.7 Sports Medical Digital Twins 561
    24.8 Personalized Athlete Care 562
    24.9 Ethical, Legal, and Social Implications (ELSI) 565
    24.10 Conclusion 567

    25 Quantum Computing and Its Role in Medical Data Processing 569
    Pratik S. Patel, Vaishali Patel and Sagar V. Fegade

    25.1 Introduction 570
    25.2 Fundamentals of Quantum Computing 571
    25.3 Architecture of Quantum Computers 573
    25.4 Medical Data Landscape 574
    25.5 Quantum Algorithms for Medical Data Processing 577
    25.6 Use Cases and Applications 579
    25.7 Integration with Classical Systems 580
    25.8 Case Studies 582
    25.9 Future Directions 584

    Conclusion 586
    References 587
    Index 589