Abhishek Kumar is Assistant Director and Professor in the Department of Computer Science and Engineering at Chandigarh University, Punjab, India. He holds a Ph.D. in Computer Science from the University of Madras and is currently a Post-Doctoral Fellow with the Ingenium Research Group, Universidad de Castilla-La Mancha, Ciudad Real, Spain. He received his M.Tech in Computer Science and Engineering and B.Tech in Information Technology from Rajasthan Technical University, Kota, India. He has over thirteen years of academic teaching experience. His research interests include Artificial Intelligence, Computer Vision, Image Processing, Data Mining, Machine Learning, and Renewable Energy Systems. Priya Batta is an Associate Professor in Amity School of Engineering and Technology, Amity University Punjab, Mohali, India. She holds a Ph.D. in Computer Science and Engineering from Chandigarh University, Mohali. She has over twelve years of academic teaching experience. Her research interests include Artificial Intelligence, Blockchain, and the Internet of Things. Dr Reyes Juárez Ramírez is a Full Professor of Computer Science at the Autonomous University of Baja California, Tijuana, Mexico. He currently serves as President of the Mexican Network of Software Engineering and is a Level 2 member of Mexico’s National System of Researchers. He leads several industry-linked research projects and specializes in applying data science to software engineering. His work focuses on uncertainty in agile methodologies, quality enhancement in Scrum, user-centered design, adaptive interfaces, and emerging research in quantum computing. He has also served as General Chair for the National and International Conference on Software Engineering Research and Innovation. Dr J. P. Ananth is Professor of Computer Science & Engineering and Director, IQAC, at Dayananda Sagar University, Bengaluru. He holds a B.E. and M.E. in Computer Science from MS University and a PhD from Sathyabama University, Chennai. With 23 years of academic experience, he has previously served as Professor and Dean–IQAC, Coimbatore, where he led NAAC Cycle II to an A++ accreditation in 2024. His research interests include Computer Vision, Pattern Recognition, AI, and Data Analytics, supported by DST-TIDE funding. He has published impactful research in reputed journals such as Expert Systems with Applications, has supervised six PhD scholars, and reviews for leading international journals and conferences.

• 1. Introduction to Federated Quantum Learning2. Foundations of Quantum Computing and Federated Learning3. Challenges in Healthcare Data Privacy and Security4. Principles and Architecture of Quantum Convolutional Neural Networks (QCNNs)5. Quantum Machine Learning for Healthcare6. Federated Quantum Convolutional Neural Networks (FedQCNNs)7. Design, Implementation, and Deployment of FedQCNNs8. Secure Communication and Aggregation Protocols9. Privacy-Preserving Methods for Healthcare Data10. Efficiency, Scalability, and Optimization Techniques11. Evaluation and Performance on Real-World Datasets12. Medical Image Analysis and Genomics Applications13. Case Studies in Real-World Healthcare Scenarios14. Quantum Noise, Error Correction, and Practical Limitations15. Integration with Classical Federated Learning Models16. Collaborative Frameworks and Institutional Deployments17. Regulatory and Legal Frameworks for FedQCNNs18. Future Directions and Impact on Healthcare Innovation

Abhishek Kumar is Assistant Director and Professor in the Department of Computer Science and Engineering at Chandigarh University, Punjab, India. He holds a Ph.D. in Computer Science from the University of Madras and is currently a Post-Doctoral Fellow with the Ingenium Research Group, Universidad de Castilla-La Mancha, Ciudad Real, Spain. He received his M.Tech in Computer Science and Engineering and B.Tech in Information Technology from Rajasthan Technical University, Kota, India. He has over thirteen years of academic teaching experience. His research interests include Artificial Intelligence, Computer Vision, Image Processing, Data Mining, Machine Learning, and Renewable Energy Systems. Priya Batta is an Associate Professor in Amity School of Engineering and Technology, Amity University Punjab, Mohali, India. She holds a Ph.D. in Computer Science and Engineering from Chandigarh University, Mohali. She has over twelve years of academic teaching experience. Her research interests include Artificial Intelligence, Blockchain, and the Internet of Things. Dr Reyes Juárez Ramírez is a Full Professor of Computer Science at the Autonomous University of Baja California, Tijuana, Mexico. He currently serves as President of the Mexican Network of Software Engineering and is a Level 2 member of Mexico’s National System of Researchers. He leads several industry-linked research projects and specializes in applying data science to software engineering. His work focuses on uncertainty in agile methodologies, quality enhancement in Scrum, user-centered design, adaptive interfaces, and emerging research in quantum computing. He has also served as General Chair for the National and International Conference on Software Engineering Research and Innovation. Dr J. P. Ananth is Professor of Computer Science & Engineering and Director, IQAC, at Dayananda Sagar University, Bengaluru. He holds a B.E. and M.E. in Computer Science from MS University and a PhD from Sathyabama University, Chennai. With 23 years of academic experience, he has previously served as Professor and Dean–IQAC, Coimbatore, where he led NAAC Cycle II to an A++ accreditation in 2024. His research interests include Computer Vision, Pattern Recognition, AI, and Data Analytics, supported by DST-TIDE funding. He has published impactful research in reputed journals such as Expert Systems with Applications, has supervised six PhD scholars, and reviews for leading international journals and conferences.

• 1. Introduction to Federated Quantum Learning2. Foundations of Quantum Computing and Federated Learning3. Challenges in Healthcare Data Privacy and Security4. Principles and Architecture of Quantum Convolutional Neural Networks (QCNNs)5. Quantum Machine Learning for Healthcare6. Federated Quantum Convolutional Neural Networks (FedQCNNs)7. Design, Implementation, and Deployment of FedQCNNs8. Secure Communication and Aggregation Protocols9. Privacy-Preserving Methods for Healthcare Data10. Efficiency, Scalability, and Optimization Techniques11. Evaluation and Performance on Real-World Datasets12. Medical Image Analysis and Genomics Applications13. Case Studies in Real-World Healthcare Scenarios14. Quantum Noise, Error Correction, and Practical Limitations15. Integration with Classical Federated Learning Models16. Collaborative Frameworks and Institutional Deployments17. Regulatory and Legal Frameworks for FedQCNNs18. Future Directions and Impact on Healthcare Innovation

Abhishek Kumar is Assistant Director and Professor in the Department of Computer Science and Engineering at Chandigarh University, Punjab, India. He holds a Ph.D. in Computer Science from the University of Madras and is currently a Post-Doctoral Fellow with the Ingenium Research Group, Universidad de Castilla-La Mancha, Ciudad Real, Spain. He received his M.Tech in Computer Science and Engineering and B.Tech in Information Technology from Rajasthan Technical University, Kota, India. He has over thirteen years of academic teaching experience. His research interests include Artificial Intelligence, Computer Vision, Image Processing, Data Mining, Machine Learning, and Renewable Energy Systems. Priya Batta is an Associate Professor in Amity School of Engineering and Technology, Amity University Punjab, Mohali, India. She holds a Ph.D. in Computer Science and Engineering from Chandigarh University, Mohali. She has over twelve years of academic teaching experience. Her research interests include Artificial Intelligence, Blockchain, and the Internet of Things. Dr Reyes Juárez Ramírez is a Full Professor of Computer Science at the Autonomous University of Baja California, Tijuana, Mexico. He currently serves as President of the Mexican Network of Software Engineering and is a Level 2 member of Mexico’s National System of Researchers. He leads several industry-linked research projects and specializes in applying data science to software engineering. His work focuses on uncertainty in agile methodologies, quality enhancement in Scrum, user-centered design, adaptive interfaces, and emerging research in quantum computing. He has also served as General Chair for the National and International Conference on Software Engineering Research and Innovation. Dr J. P. Ananth is Professor of Computer Science & Engineering and Director, IQAC, at Dayananda Sagar University, Bengaluru. He holds a B.E. and M.E. in Computer Science from MS University and a PhD from Sathyabama University, Chennai. With 23 years of academic experience, he has previously served as Professor and Dean–IQAC, Coimbatore, where he led NAAC Cycle II to an A++ accreditation in 2024. His research interests include Computer Vision, Pattern Recognition, AI, and Data Analytics, supported by DST-TIDE funding. He has published impactful research in reputed journals such as Expert Systems with Applications, has supervised six PhD scholars, and reviews for leading international journals and conferences.

• 1. Introduction to Federated Quantum Learning2. Foundations of Quantum Computing and Federated Learning3. Challenges in Healthcare Data Privacy and Security4. Principles and Architecture of Quantum Convolutional Neural Networks (QCNNs)5. Quantum Machine Learning for Healthcare6. Federated Quantum Convolutional Neural Networks (FedQCNNs)7. Design, Implementation, and Deployment of FedQCNNs8. Secure Communication and Aggregation Protocols9. Privacy-Preserving Methods for Healthcare Data10. Efficiency, Scalability, and Optimization Techniques11. Evaluation and Performance on Real-World Datasets12. Medical Image Analysis and Genomics Applications13. Case Studies in Real-World Healthcare Scenarios14. Quantum Noise, Error Correction, and Practical Limitations15. Integration with Classical Federated Learning Models16. Collaborative Frameworks and Institutional Deployments17. Regulatory and Legal Frameworks for FedQCNNs18. Future Directions and Impact on Healthcare Innovation