Gans For Data Augmentation In Healthcare
DOWNLOAD
Download Gans For Data Augmentation In Healthcare PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Gans For Data Augmentation In Healthcare book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Gans For Data Augmentation In Healthcare
DOWNLOAD
Author : Arun Solanki
language : en
Publisher: Springer Nature
Release Date : 2023-11-13
Gans For Data Augmentation In Healthcare written by Arun Solanki and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-13 with Medical categories.
Computer-Assisted Diagnostics (CAD) using Convolutional Neural Network (CNN) model has become an important technology in the medical industry, improving the accuracy of diagnostics. However, the lack Magnetic Resonance Imaging (MRI) data leads to the failure of the depth study algorithm. Medical records are often different because of the cost of obtaining information and the time spent consuming the information. In general, clinical data is unreliable and therefore the training of neural network methods to distribute disease across classes does not yield the desired results. Data augmentation is often done by training data to solve problems caused by augmentation tasks such as scaling, cropping, flipping, padding, rotation, translation, affine transformation, and color augmentation techniques such as brightness, contrast, saturation, and hue. Data Augmentation and Segmentation imaging using GAN can be used to provide clear images of brain, liver, chest, abdomen, and liver on an MRI. In addition, GAN shows strong promise in the field of clinical image synthesis. In many cases, clinical evaluation is limited by a lack of data and/or the cost of actual information. GAN can overcome these problems by enabling scientists and clinicians to work on beautiful and realistic images. This can improve diagnosis, prognosis, and disease. Finally, GAN highlights the potential for location of patient information within the data. This is a beneficial clinical application of GAN because it can effectivelyprotect patient confidentiality. This book covers the application of GANs on medical imaging augmentation and segmentation.
Advanced Machine Learning For Complex Medical Data Analysis
DOWNLOAD
Author : Saumendra Kumar Mohapatra, Mihir Narayan Mohanty, Rashmita Khilar
language : en
Publisher: Bentham Science Publishers
Release Date : 2025-05-13
Advanced Machine Learning For Complex Medical Data Analysis written by Saumendra Kumar Mohapatra, Mihir Narayan Mohanty, Rashmita Khilar and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-13 with Computers categories.
Advanced Machine Learning for Complex Medical Data Analysis is a definitive guide to leveraging machine learning to solve critical challenges in medical data analysis. This book discusses cutting-edge methodologies, from predictive modeling to neural networks, tailored to address the unique complexities of medical and healthcare data. It combines theoretical frameworks with practical applications, ensuring readers gain a comprehensive understanding of both concepts and real-world implementations. The book covers diverse topics, including medical image denoising, the transformative role of GANs, IoT applications in healthcare, early disease detection using speech data, and COVID detection using autoencoders. It also explores the impact of big data, statistical approaches to medical analytics, and public health improvements through technology. Key Features: - Practical insights into deploying advanced machine learning models for healthcare. - Real-world case studies on diverse diseases and datasets. - Cutting-edge topics like explainable AI, federated learning, and ethical considerations. - Methods for improving data accuracy, efficiency, and privacy.
Revolutionizing Healthcare 5 0 The Power Of Generative Ai
DOWNLOAD
Author : Pronaya Bhattacharya
language : en
Publisher: Springer Nature
Release Date : 2025-02-18
Revolutionizing Healthcare 5 0 The Power Of Generative Ai written by Pronaya Bhattacharya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-18 with Technology & Engineering categories.
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.
Machine Learning And Generative Ai In Smart Healthcare
DOWNLOAD
Author : Purushotham, Swarnalatha
language : en
Publisher: IGI Global
Release Date : 2024-08-28
Machine Learning And Generative Ai In Smart Healthcare written by Purushotham, Swarnalatha and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-28 with Medical categories.
The healthcare landscape is constantly evolving, and one of the most significant concerns that healthcare professionals deal with is understanding how to use biomedical intelligence to improve patient outcomes. With the increasing complexity of healthcare computing systems, including technologies like deep learning and the Internet of Things, it can be challenging to navigate these advancements. Machine Learning and Generative AI in Smart Healthcare is a practical tool for healthcare professionals, researchers, and policymakers who are seeking to implement biomedical intelligence solutions. It provides a clear roadmap for using prescriptive and predictive analytics in machine learning to enhance healthcare outcomes. Going beyond the basics, it delves into healthcare computing and networking complexities. By delving into topics such as data mining, disease prediction, and AI applications, deep learning approaches, decision support systems, and optimization techniques, this book equips readers with the practical knowledge they need to optimize healthcare delivery and management.
Artificial Intelligence Revolutionizing Cancer Care
DOWNLOAD
Author : Suman Kumar Swarnkar
language : en
Publisher: CRC Press
Release Date : 2025-02-25
Artificial Intelligence Revolutionizing Cancer Care written by Suman Kumar Swarnkar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-25 with Technology & Engineering categories.
In the ever-evolving landscape of cancer treatment, the fusion of artificial intelligence (AI) with medical science marks a groundbreaking shift toward more precise, efficient, and personalized healthcare. Artificial Intelligence Revolutionizing Cancer Care: Precision Diagnosis and Patient-Centric Healthcare delves into the transformative power of AI, offering a comprehensive exploration of its role in enhancing cancer diagnosis, treatment, and patient management. This edited volume brings together leading experts and researchers who illuminate the latest advancements in AI technologies applied to oncology. From machine learning algorithms that predict cancer progression to sophisticated imaging techniques that improve diagnostic accuracy, this book covers a spectrum of innovations reshaping cancer care. Key highlights include precision diagnosis, uncovering how AI-driven tools are revolutionizing the early detection and accurate classification of various cancer types, leading to better patient outcomes; patient-centric approaches, exploring the shift toward personalized medicine, where AI tailors treatment protocols to individual patient profiles, ensuring more effective and targeted therapies; and ethical and practical considerations, gaining insights into the ethical, practical, and regulatory challenges of integrating AI in healthcare, emphasizing the need for patient privacy and data security. Additionally, the book looks ahead to the potential future applications of AI in oncology, including predictive analytics, robotic surgery, and beyond. Artificial Intelligence Revolutionizing Cancer Care is an essential resource for medical professionals, researchers, and students seeking to understand the intersection of AI and oncology. It offers a visionary perspective on how cutting-edge technology is poised to enhance patient care and transform the fight against cancer. This book focuses on the critical intersection of artificial intelligence and cancer diagnosis within the healthcare sector emphasizes the real-world impact of artificial intelligence in improving cancer detection, treatment, and overall patient care covers artificial intelligence algorithms, machine learning techniques, medical image analysis, predictive modeling, and patient care applications explores how artificial intelligence technologies enhance the patient’s experience, resulting in better outcomes and reduced healthcare disparities provides readers with an understanding of the mathematics underpinning machine learning models, including decision trees, support vector machines, and deep neural networks It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, biomedical engineering, and information technology.
Utilizing Ai Of Medical Things For Healthcare Security And Sustainability
DOWNLOAD
Author : Ouaissa, Mariyam
language : en
Publisher: IGI Global
Release Date : 2025-04-11
Utilizing Ai Of Medical Things For Healthcare Security And Sustainability written by Ouaissa, Mariyam and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-11 with Medical categories.
The integration of AI and IoT in healthcare, particularly through the Internet of Medical Things (IoMT), is revolutionizing medical care by enhancing efficiency and personalization. These technologies enable more accurate patient monitoring, streamlined healthcare delivery, and customized treatment plans that address individual needs. With the ability to analyze vast amounts of patient data in real-time, AIoMT is improving diagnostics, outcomes, and the overall patient experience. This transformation holds significant potential to reduce healthcare costs, alleviate the burden on traditional systems, and improve overall public health. By fostering smarter healthcare practices, AIoMT is helping to shape a more responsive, efficient, and accessible medical landscape. Utilizing AI of Medical Things for Healthcare Security and Sustainability explores the transformative role of AI and IoMT in modern healthcare. It delves into how AI-driven technologies and smart medical devices are revolutionizing patient care through real-time monitoring, predictive analytics, and personalized treatment plans. Covering topics such as autonomous vehicles, disease prediction, and wearable health technology, this book is an excellent resource for researchers, healthcare professionals, academicians, technologists, and more.
Big Data Analytics And Artificial Intelligence In The Healthcare Industry
DOWNLOAD
Author : Machado, José
language : en
Publisher: IGI Global
Release Date : 2022-04-29
Big Data Analytics And Artificial Intelligence In The Healthcare Industry written by Machado, José and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-29 with Computers categories.
Developing new approaches and reliable enabling technologies in the healthcare industry is needed to enhance our overall quality of life and lead to a healthier, innovative, and secure society. Further study is required to ensure these current technologies, such as big data analytics and artificial intelligence, are utilized to their utmost potential and are appropriately applied to advance society. Big Data Analytics and Artificial Intelligence in the Healthcare Industry discusses technologies and emerging topics regarding reliable and innovative solutions applied to the healthcare industry and considers various applications, challenges, and issues of big data and artificial intelligence for enhancing our quality of life. Covering a range of topics such as electronic health records, machine learning, and e-health, this reference work is ideal for healthcare professionals, computer scientists, data analysts, researchers, practitioners, scholars, academicians, instructors, and students.
Application Of Generative Ai In Healthcare Systems
DOWNLOAD
Author : Azadeh Zamanifar
language : en
Publisher: Springer Nature
Release Date : 2025-02-25
Application Of Generative Ai In Healthcare Systems written by Azadeh Zamanifar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-25 with Medical categories.
Generative AI has immensely influenced various fields, such as education, marketing, art and music, and especially healthcare. Generative AI can benefit the patient through various approaches. For instance, it can enhance the image qualities negatively affected by radiation reduction, preventing patients from needing to repeat the image-taking process. Also, the generation of one type of image from another more expensive one can help patients save funds. Generative AI facilitates the administrative process, letting the doctor focus more on the treatment process. It even goes further by helping medical professionals with diagnosis and decision- making, suggesting possible treatment plans according to the patient symptoms. This book introduces several practical GenAI healthcare applications, especially in medical imaging, pandemic prediction, synthetic data generation, clinical administration support, professional education, patient engagement, and clinical decision support, providing a review of efficient GenAI tools and frameworks in this area. GenAI empowers the treatment process through several methods; however, some ethical, privacy, and security challenges require attention. Despite the challenges presented, GenAI technological and inherited characteristics smooth the path of improvement for it in the future.
Intelligent Healthcare Systems
DOWNLOAD
Author : Vania V. Estrela
language : en
Publisher: CRC Press
Release Date : 2023-08-04
Intelligent Healthcare Systems written by Vania V. Estrela and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-04 with Computers categories.
The book sheds light on medical cyber-physical systems while addressing image processing, microscopy, security, biomedical imaging, automation, robotics, network layers’ issues, software design, and biometrics, among other areas. Hence, solving the dimensionality conundrum caused by the necessity to balance data acquisition, image modalities, different resolutions, dissimilar picture representations, subspace decompositions, compressed sensing, and communications constraints. Lighter computational implementations can circumvent the heavy computational burden of healthcare processing applications. Soft computing, metaheuristic, and deep learning ascend as potential solutions to efficient super-resolution deployment. The amount of multi-resolution and multi-modal images has been augmenting the need for more efficient and intelligent analyses, e.g., computer-aided diagnosis via computational intelligence techniques. This book consolidates the work on artificial intelligence methods and clever design paradigms for healthcare to foster research and implementations in many domains. It will serve researchers, technology professionals, academia, and students working in the area of the latest advances and upcoming technologies employing smart systems’ design practices and computational intelligence tactics for medical usage. The book explores deep learning practices within particularly difficult computational types of health problems. It aspires to provide an assortment of novel research works that focuses on the broad challenges of designing better healthcare services.
Dhealth 2020 Biomedical Informatics For Health And Care
DOWNLOAD
Author : G. Schreier
language : en
Publisher: IOS Press
Release Date : 2020-06-24
Dhealth 2020 Biomedical Informatics For Health And Care written by G. Schreier and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-24 with Medical categories.
Successful digital healthcare depends on the effective flow of a complete chain of information; from the sensor, via multiple steps of processing, to the actuator, which can be anything from a human healthcare professional to a robot. Along this pathway, methods for automating the processing of information, like signal processing, machine learning, predictive analytics and decision support, play an increasing role in providing actionable information and supporting personalized and preventive healthcare concepts in both biomedical and digital healthcare systems and applications. ICT systems in healthcare and biomedical systems and devices are very closely related, and in the future they will become increasingly intertwined. Indeed, it is already often difficult to delineate where the one ends and the other begins. This book presents the intended proceedings of the dHealth 2020 annual conference on the general topic of health Informatics and digital health, which was due to be held in Vienna, Austria, on 19 and 20 May 2020, but which was cancelled due to the COVID-19 pandemic. The decision was nevertheless taken to publish these proceedings, which include the 40 papers which would have been delivered at the conference. The special topic for the 2020 edition of the conference was Biomedical Informatics for Health and Care. The book provides an overview of current developments in health informatics and digital health, and will be of interest to researchers and healthcare practitioners alike.