Advances In Deep Generative Models For Medical Artificial Intelligence
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Advances In Deep Generative Models For Medical Artificial Intelligence
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Author : Hazrat Ali
language : en
Publisher: Springer Nature
Release Date : 2023-12-16
Advances In Deep Generative Models For Medical Artificial Intelligence written by Hazrat Ali and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-16 with Computers categories.
Generative Artificial Intelligence is rapidly advancing with many state-of-the-art performances on computer vision, speech processing, and natural language processing tasks. Generative adversarial networks and neural diffusion models can generate high-quality synthetic images of human faces, artworks, and coherent essays on different topics. Generative models are also transforming Medical Artificial Intelligence, given their potential to learn complex features from medical imaging and healthcare data. Hence, computer-aided diagnosis and healthcare are benefiting from Medical Artificial Intelligence and Generative Artificial Intelligence. This book presents the recent advances in generative models for Medical Artificial Intelligence. It covers many applications of generative models for medical image data, including volumetric medical image segmentation, data augmentation, MRI reconstruction, and modeling of spatiotemporal medical data. This book highlights the recent advancements in Generative Artificial Intelligence for medical and healthcare applications, using medical imaging and clinical and electronic health records data. Furthermore, the book comprehensively presents the concepts and applications of deep learning-based artificial intelligence methods, such as generative adversarial networks, convolutional neural networks, and vision transformers. It also presents a quantitative and qualitative analysis of data augmentation and synthesis performances of Generative Artificial Intelligence models. This book is the result of the collaborative efforts and hard work of many minds who contributed to it and illuminated the vast landscape of Medical Artificial Intelligence. The book is suitable for reading by computer science researchers, medical professionals, healthcare informatics, and medical imaging researchers interested in understanding the potential of artificial intelligence in healthcare. It serves as a compass for navigating the artificial intelligence-driven healthcare landscape.
Deep Generative Models
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Author : Anirban Mukhopadhyay
language : en
Publisher: Springer Nature
Release Date : 2024-02-19
Deep Generative Models written by Anirban Mukhopadhyay and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-19 with Computers categories.
This LNCS conference volume constitutes the proceedings of the third MICCAI Workshop, DGM4MICCAI 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 2023. The 23 full papers included in this volume were carefully reviewed and selected from 38 submissions. The conference presents topics ranging from methodology, causal inference, latent interpretation, generative factor analysis to applications such as mammography, vessel imaging, and surgical Videos.
Generative Artificial Intelligence For Biomedical And Smart Health Informatics
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Author : Aditya Khamparia
language : en
Publisher: John Wiley & Sons
Release Date : 2025-02-05
Generative Artificial Intelligence For Biomedical And Smart Health Informatics written by Aditya Khamparia and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-05 with Medical categories.
Enables readers to understand the future of medical applications with generative AI and related applications Generative Artificial Intelligence for Biomedical and Smart Health Informatics delivers a comprehensive overview of the most recent generative AI-driven medical applications based on deep learning and machine learning in which biomedical data is gathered, processed, and analyzed using data augmentation techniques. This book covers many applications of generative models for medical image data, including volumetric medical image segmentation, data augmentation, MRI reconstruction, and modeling of spatiotemporal medical data. The book explores findings obtained by explainable AI techniques, with coverage of various techniques rarely reported in literature. Throughout, feedback and user experiences from physicians and medical staff, as well as use cases, are included to provide important context. The book discusses topics including privacy and security challenges in AI-enabled health informatics, biosensor-guided AI interventions in personalized medicine, regulatory frameworks and guidelines for AI-based medical devices, education and training for building responsible AI solutions in healthcare, and challenges and opportunities in integrating generative AI with wearable devices. Topics covered include: Treatment of neurological disorders using intelligent techniques and image-guided and tomography interventions for neuromuscular disorders Bio-inspired smart healthcare service frameworks with AI, machine learning, and deep learning, integration of IoT devices, and edge computing in industrial and clinical systems Traffic management and optimization in distributed environments, patient data management, disease surveillance and prediction, and telemedicine and remote monitoring Education-driven, peer-to-peer, and service-oriented architectures and transparency and accountability in medical decision-making Generative Artificial Intelligence for Biomedical and Smart Health Informatics is an essential reference for computer science researchers, medical professionals, healthcare informatics, and medical imaging researchers interested in understanding the potential of artificial intelligence and other related technologies in healthcare.
Revolutionizing Medical Systems Using Artificial Intelligence
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Author : Ashish Kumar
language : en
Publisher: Elsevier
Release Date : 2025-01-31
Revolutionizing Medical Systems Using Artificial Intelligence written by Ashish Kumar and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-31 with Science categories.
Revolutionizing Medical Systems using Artificial Intelligence: A Breakthrough in Healthcare provides an overview of various machine learning and deep learning techniques, addressing the needs of patients and the necessity for medical aid at early stages of disease. The book reviews, analyzes, and compares the different methodologies utilized for the prediction and detection of diseases. In addition, it explores the possible deployment of these advancements in medical systems, from paper to practice. With the advent of technology, tele consultation, telemedicine, and mobile health care, it is now possible to provide continuous monitoring of the health of patients.This title fulfills the needs of connected healthcare systems, providing insights into the role of Artificial Intelligence in the prognosis, diagnosis, and analysis of several diseases. It will be a valuable resource for health professionals, scientists and researchers, health practitioners, students, and all those who wish to broaden their knowledge in the challenging field of artificial intelligence in medical systems and diseases. - Provides a wide range of coverage for various prediction and segmentation algorithms that are based on machine learning and deep learning technology - Covers various predictive and segmentation algorithms exploited by various medical personnel to improve the accuracy of treatment to the patients - Highlights improvements in quality and efficiency of medical decision-making in the early detection of critical diseases using AI
Advanced Network Technologies And Intelligent Computing
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Author : Anshul Verma
language : en
Publisher: Springer Nature
Release Date : 2024-08-07
Advanced Network Technologies And Intelligent Computing written by Anshul Verma and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-07 with Computers categories.
The 4-volume proceedings set CCIS 2090, 2091,2092 and 2093 constitute the refereed post-conference proceedings of the Third International Conference on Advanced Network Technologies and Intelligent Computing, ANTIC 2023, held in Varanasi, India, during December 20-22, 2023. The 87 full papers and 11 short papers included in this book were carefully reviewed and selected from 487 submissions. The conference papers are organized in topical sections on: Part I - Advanced Network Technologies. Part II - Advanced Network Technologies; Intelligent Computing. Part III - IV - Intelligent Computing.
Principles And Methods Of Explainable Artificial Intelligence In Healthcare
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Author : Albuquerque, Victor Hugo C. de
language : en
Publisher: IGI Global
Release Date : 2022-05-20
Principles And Methods Of Explainable Artificial Intelligence In Healthcare written by Albuquerque, Victor Hugo C. de and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-20 with Computers categories.
Explainable artificial intelligence is proficient in operating and analyzing the unconstrainted environment in fields like robotic medicine, robotic treatment, and robotic surgery, which rely on computational vision for analyzing complex situations. Explainable artificial intelligence is a well-structured customizable technology that makes it possible to generate promising unbiased outcomes. The model’s adaptability facilitates the management of heterogeneous healthcare data and the visualization of biological structures through virtual reality. Explainable artificial intelligence has newfound applications in the healthcare industry, such as clinical trial matching, continuous healthcare monitoring, probabilistic evolutions, and evidence-based mechanisms. Principles and Methods of Explainable Artificial Intelligence in Healthcare discusses explainable artificial intelligence and its applications in healthcare, providing a broad overview of state-of-the-art approaches for accurate analysis and diagnosis. The book also encompasses computational vision processing techniques that handle complex data like physiological information, electronic healthcare records, and medical imaging data that assist in earlier prediction. Covering topics such as neural networks and disease detection, this reference work is ideal for industry professionals, practitioners, academicians, researchers, scholars, instructors, and students.
Generative Intelligence In Healthcare
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Author : Sakshi Gupta
language : en
Publisher: CRC Press
Release Date : 2025-04-10
Generative Intelligence In Healthcare written by Sakshi Gupta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-10 with Technology & Engineering categories.
This book explores the intersection of artificial intelligence and healthcare with a focus on generative intelligence. The book will introduce the concept of generative intelligence and its transformative potential in patient care, showcasing applications that go beyond conventional AI approaches. Generative Intelligence in Healthcare: Transforming Patient Care with AI Creativity delves into the use of generative models for personalized medicine, data analytics, and predictive modelling, providing real-world examples of how AI creativity can revolutionize treatment strategies and diagnostic processes. It focuses on the origin and basics of generative AI, generative AI models, and possible areas in healthcare where generative AI can work. It discusses how generative AI model will help healthcare providers automatically generate prescriptions, discharge summaries, and patient conditions. The unique strength of this book lies in its comprehensive examination of ethical considerations and regulatory frameworks, ensuring a responsible and transparent integration of generative intelligence in healthcare. By addressing current challenges and envisioning future directions, this book serves as a valuable resource for healthcare professionals, researchers, and policymakers seeking to harness the full potential of AI creativity to enhance patient outcomes. The book is written for graduate students, researchers, and professionals in biomedical engineering, electrical engineering, signal process engineering, biomedical imaging, and computer science.
Web Artificial Intelligence And Network Applications
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Author : Leonard Barolli
language : en
Publisher: Springer
Release Date : 2019-03-14
Web Artificial Intelligence And Network Applications written by Leonard Barolli and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-14 with Computers categories.
The aim of the book is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of Web Computing, Intelligent Systems and Internet Computing. As the Web has become a major source of information, techniques and methodologies that extract quality information are of paramount importance for many Web and Internet applications. Data mining and knowledge discovery play key roles in many of today’s prominent Web applications such as e-commerce and computer security. Moreover, the outcome of Web services delivers a new platform for enabling service-oriented systems. The emergence of large scale distributed computing paradigms, such as Cloud Computing and Mobile Computing Systems, has opened many opportunities for collaboration services, which are at the core of any Information System. Artificial Intelligence (AI) is an area of computer science that build intelligent systems and algorithms that work and react like humans. The AI techniques and computational intelligence are powerful tools for learning, adaptation, reasoning and planning. They have the potential to become enabling technologies for the future intelligent networks. Recent research in the field of intelligent systems, robotics, neuroscience, artificial intelligence and cognitive sciences are very important for the future development and innovation of Web and Internet applications.
Revolutionizing The Healthcare Sector With Ai
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Author : Singla, Babita
language : en
Publisher: IGI Global
Release Date : 2024-07-26
Revolutionizing The Healthcare Sector With Ai written by Singla, Babita and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-26 with Medical categories.
The healthcare sector is at a critical juncture, facing the pressing need to integrate generative AI technologies responsibly. Despite the promising benefits, such as improved diagnostics, personalized treatments, and streamlined operations, the adoption of AI in healthcare poses significant challenges. These challenges include ethical dilemmas, regulatory complexities, and the need for governance frameworks to ensure the technology's responsible use. Revolutionizing the Healthcare Sector with AI offers a comprehensive solution to these challenges. It provides a deep dive into the adoption, integration, scalability, and sustainability of generative AI in healthcare and a thorough analysis of governance, ethical, and regulatory issues. By offering insights from researchers, practitioners, patients, and policymakers, this book is a platform for responsible AI adoption in healthcare.
Scalable Artificial Intelligence For Healthcare
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Author : Houneida Sakly
language : en
Publisher: CRC Press
Release Date : 2025-05-06
Scalable Artificial Intelligence For Healthcare written by Houneida Sakly and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-06 with Computers categories.
This edited volume examines the transformative impact of AI technologies on global healthcare systems, with a focus on enhancing efficiency and accessibility. The content provides a comprehensive exploration of the principles and practices required to scale AI applications in healthcare, addressing areas such as diagnosis, treatment, and patient care. Key topics include data scalability, model deployment, and infrastructure design, highlighting the use of microservices, containerization, cloud computing, and big data technologies in building scalable AI systems. Discussions cover advancements in machine learning models, distributed processing, and transfer learning, alongside critical considerations such as continuous integration, data privacy, and ethics. Real-world case studies depict both the successes and challenges of implementing scalable AI across various healthcare environments, offering valuable insights for future advancements. This volume serves as a practical and theoretical guide for healthcare professionals, AI researchers, and technology enthusiasts seeking to develop or expand on AI-driven healthcare solutions to address global health challenges effectively.