Revolutionizing healthcare 5.0: the power of generative AI: advancements in patient care through generative AI algorithms
- Cham Springer 2024
- ix, 476 p.
- Studies in Systems, Decision and Control (SSDC, volume 571) .
Table of contents: Front Matter Pages i-ix Download chapter PDF A Systematic Review on Learning Based Models for Automatic Classification of Medical Documents Suwarna Gothane, B. Sivaneasan, Amjan Shaik, Prasun Chakrabarti Pages 1-11 A Novel Method for Automatic Detection of Ulcer in Wireless Capsule Endoscopy Images C. P. Sindhu, Vysak Valsan Pages 13-26 GAN-Enhanced Deep Learning Framework for High-Precision Lung Nodule Detection and Severity Assessment in CT Images A. Asuntha, P. K. Dutta, K. Vino Aishwarya Pages 27-56 Machine Learning Approach to Recognition Human Mental State from EEG Signal Swati Chowdhuri, Ayushi Bhargav, Ayan Kumar Panja, Amartya Mukherjee Pages 57-75 Maximizing Accuracy in Alzheimer’s Disease Prediction: A Optuna Hyper Parameter Optimization Strategy Using MRI Images P. Deepan, G. Prabhakar Reddy, M. Arsha Reddy, R. Vidya, S. Dhiravidaselvi Pages 77-91 Advanced Deep Learning Models for COVID-19 Prediction: A Multi-convolutional Neural Network Perspective P. Deepan, Amjan Shaik, R. Santhoshkumar, B. Rajalingam, S. Dhiravidaselvi, N. Arul Pages 93-109 A Parametric Analysis of Cardiovascular Diseases Detection Methods Using ML Techniques Marri Sireesha, Anjaiah Adepu, Amjan Shaik, Naga Jyothi Pages 111-123 Machine Learning Based Disease Classification and Prediction Sandhya Nadella, Pushkara Annaldas, Sai Aashritha Kalakancheri, Charan Sai Kamsani, Jagruthi Mekala Pages 125-137 Segmentation of Retinal Blood Vessels and Optic Disc Using Deep Neural Networks: State-Of-The-Art Review Saba Sheiba, M. Neelakantappa, Amjan Shaik Pages 139-152 Enhancing Brain Tumor Detection in MR Images Using Modified Few-Shot Learning Akkipalli Sowjanya, Amjan Shaik Pages 153-163 An Empirical Study on Lung Cancer Detection and Classification Using Machine Learning and Image Processing Techniques Kabir Ahmed, Syed Sazzad Ahmed, Abhishek Talukdar, Dipraj Chakrabarty Pages 165-176 Survey on Depression Detection Using Machine Learning Techniques⋆ Kritika Shrivastava, Arunima Jaiswal, Nitin Sachdeva Pages 177-187 Generative AI for Enhanced Decision Making in Healthcare 5.0 C. Rajan, H. Blankson Pages 189-197 Integration of Generative AI System to IoT Based Healthcare Systems 5.0 Janjhyam Venkata Naga Ramesh, Veera Talukdar, Ardhariksa Zukhruf Kurniullah, Sanjiv Kumar Jain, Rohit Anand, Ankur Gupta Pages 199-217 Beyond Prediction: How Generative AI is Creating New Healthcare Realities Bablu Pramanik, Debosree Ghosh, Debasree Ghosh, Kaushik Paul Pages 219-233 Vertical Integration of Data Augmentation Using Generative AI in Medical Imagining for Population Health: Deep Learning Approaches for Transforming Health 5.0 Bhupinder Singh, Pushan Kumar Dutta, Christian Kaunert Pages 235-253 Securing Healthcare AI: Applied Federal Learning Md. Nurul Huda, Mohammad Badruddoza Talukder, Sanjeev Kumar Pages 255-272 Enhancing Healthcare Operations: Harnessing Generative AI for Efficiency and Innovation Pawan Whig, Pushan Kumar Dutta, Nikhitha Yathiraju, Pronaya Bhattacharya, Iti Batra Pages 273-287 Transforming Healthcare Operations with Generative AI: Optimizing Resource Allocation, Workflow Management, and Predictive Analytics Pawan Whig, Pushan Kumar Dutta, Nikhitha Yathiraju, Pronaya Bhattacharya, Seema Sharma Pages 289-308 Implementation of Novel Voice Cloning Method Based on Comprehensive Review of Voice Cloning Technologies: Methodology, Applications, and Future Directions Ch Pavan Harshit, Satvik Yadav Elitem, M. Venakata Krishna Reddy Pages 309-320 Emerging Role of Blockchain in Generative AI for Healthcare Management Shivi Khanna, Nabanita Ghosh, Sunita Kumar Pages 321-336 Prioritizing Disease Screening in Health 5:0 and Pandemic Outbreak Management: Hustler Artificial Intelligence Approaches Transforming Population Healthcare Bhupinder Singh, Pushan Kumar Dutta, Christian Kaunert Pages 337-356 Predictive Models for Non-communicable Diseases: Exploring the Roles of Machine Learning, Deep Learning, Generative AI, and Optimization C. Rajeev, Karthika Natarajan Pages 357-377 Metamorphic Marvels with GAN-Powered Real-Time Image Cartoonification and Transformation for Precision Medicine BJD Kalyani, Sarabu Neelima Pages 379-388 Bridging Vision and Technology: The Future of AI in Assisting the Visually Impaired Abhishek M. Nair, Jettin Daisy Joy, S. Navaneeth, Priya Philip, S. N. Kumar, Vinu Sankar et al. Pages 389-401 Enhanced Encryption Scheme for Cloud-Based Health Care Data U. D. Rana, H. P. Gohil Pages 403-414 Enhancing Healthcare Insights Through Integration of AI and Covering-Based Rough Set Theory in Web Mining Subrata Paul, Anirban Mitra, Shivnath Ghosh Pages 415-438 Personal Nutritionist Gui for Diet Recommendation System Using Ensemble Machine Learning Technique Based on User Health Information P T Sharath, Sasi Gowtham Reddy Sathi, K. Anita Davamani Pages 439-452 Healthcare Data Encryption Based on Secure AI Model with Computational Analysis Using Machine Learning Algorithms Nattar Kannan, Ramesh Sundar, M. Rammorthy, Sulaima Lebbe Abdul Haleem, R. Manikandan Pages 453-476
This book serves as a critical resource that bridges the gap between burgeoning technology and its practical implementation. The book starts with an in-depth exploration of healthcare 5.0 principles, laying the foundation for the reader to understand the current shifts in healthcare paradigms. Then, it dives into the intricacies of generative models in healthcare, detailing how these algorithms work and the applications they serve. The book further delves into the subsets of generative machine learning and deep learning techniques in healthcare. As we move towards more complex applications, the book takes a turn to address the critical subject of interpretability and explainability in generative models, a topic that resonates profoundly given the life-critical nature of medical decisions. Finally, the book concludes with a robust discussion on the security and privacy concerns that accompany the deployment of GAI in real healthcare settings. By offering a multidimensional viewpoint—coupled with case studies, statistical analyses, and expert insights—the book ensures that the reader is left with a nuanced understanding of how GAI can be both a boon and a challenge in healthcare. As such, the proposed book serves as an indispensable resource for healthcare professionals, data scientists, researchers, and anyone invested in the future of healthcare and AI