Ai In Biological And Biomedical Imaging


Ai In Biological And Biomedical Imaging
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Ai In Biological And Biomedical Imaging


Ai In Biological And Biomedical Imaging
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Author : Xin Gao
language : en
Publisher: Frontiers Media SA
Release Date : 2022-01-17

Ai In Biological And Biomedical Imaging written by Xin Gao and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-17 with Science categories.


Doctors Gao and Li hold patents related to artificial intelligence.



Artificial Intelligence In Healthcare And Medicine


Artificial Intelligence In Healthcare And Medicine
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Author : Kayvan Najarian
language : en
Publisher: CRC Press
Release Date : 2022-04-06

Artificial Intelligence In Healthcare And Medicine written by Kayvan Najarian and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-06 with Computers categories.


This book provides a comprehensive overview of the recent developments in clinical decision support systems, precision health, and data science in medicine. The book targets clinical researchers and computational scientists seeking to understand the recent advances of artificial intelligence (AI) in health and medicine. Since AI and its applications are believed to have the potential to revolutionize healthcare and medicine, there is a clear need to explore and investigate the state-of-the-art advancements in the field. This book provides a detailed description of the advancements, challenges, and opportunities of using AI in medical and health applications. Over 10 case studies are included in the book that cover topics related to biomedical image processing, machine learning for healthcare, clinical decision support systems, visualization of high dimensional data, data security and privacy, bioinformatics, and biometrics. The book is intended for clinical researchers and computational scientists seeking to understand the recent advances of AI in health and medicine. Many universities may use the book as a secondary training text. Companies in the healthcare sector can greatly benefit from the case studies covered in the book. Moreover, this book also: Provides an overview of the recent developments in clinical decision support systems, precision health, and data science in medicine Examines the advancements, challenges, and opportunities of using AI in medical and health applications Includes 10 cases for practical application and reference Kayvan Najarian is a Professor in the Department of Computational Medicine and Bioinformatics, Department of Electrical Engineering and Computer Science, and Department of Emergency Medicine at the University of Michigan, Ann Arbor. Delaram Kahrobaei is the University Dean for Research at City University of New York (CUNY), a Professor of Computer Science and Mathematics, Queens College CUNY, and the former Chair of Cyber Security, University of York. Enrique Domínguez is a professor in the Department of Computer Science at the University of Malaga and a member of the Biomedical Research Institute of Malaga. Reza Soroushmehr is a Research Assistant Professor in the Department of Computational Medicine and Bioinformatics and a member of the Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor.



Deep Learning In Biomedical And Health Informatics


Deep Learning In Biomedical And Health Informatics
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Author : M. A. Jabbar
language : en
Publisher: CRC Press
Release Date : 2021-09-26

Deep Learning In Biomedical And Health Informatics written by M. A. Jabbar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-26 with Computers categories.


This book provides a proficient guide on the relationship between Artificial Intelligence (AI) and healthcare and how AI is changing all aspects of the healthcare industry. It also covers how deep learning will help in diagnosis and the prediction of disease spread. The editors present a comprehensive review of research applying deep learning in health informatics in the fields of medical imaging, electronic health records, genomics, and sensing, and highlights various challenges in applying deep learning in health care. This book also includes applications and case studies across all areas of AI in healthcare data. The editors also aim to provide new theories, techniques, developments, and applications of deep learning, and to solve emerging problems in healthcare and other domains. This book is intended for computer scientists, biomedical engineers, and healthcare professionals researching and developing deep learning techniques. In short, the volume : Discusses the relationship between AI and healthcare, and how AI is changing the health care industry. Considers uses of deep learning in diagnosis and prediction of disease spread. Presents a comprehensive review of research applying deep learning in health informatics across multiple fields. Highlights challenges in applying deep learning in the field. Promotes research in ddeep llearning application in understanding the biomedical process. Dr.. M.A. Jabbar is a professor and Head of the Department AI&ML, Vardhaman College of Engineering, Hyderabad, Telangana, India. Prof. (Dr.) Ajith Abraham is the Director of Machine Intelligence Research Labs (MIR Labs), Auburn, Washington, USA. Dr.. Onur Dogan is an assistant professor at İzmir Bakırçay University, Turkey. Prof. Dr. Ana Madureira is the Director of The Interdisciplinary Studies Research Center at Instituto Superior de Engenharia do Porto (ISEP), Portugal. Dr.. Sanju Tiwari is a senior researcher at Universidad Autonoma de Tamaulipas, Mexico.



Artificial Intelligence Applied To Medical Imaging And Computational Biology


Artificial Intelligence Applied To Medical Imaging And Computational Biology
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Author : Leonardo Rundo
language : en
Publisher: Mdpi AG
Release Date : 2023-02-21

Artificial Intelligence Applied To Medical Imaging And Computational Biology written by Leonardo Rundo and has been published by Mdpi AG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-21 with Science categories.


Medical imaging and computational biology continuously pose new fundamental medical and biological questions that often give rise to novel challenges in Artificial Intelligence. These research fields present an increasing need for the application of cutting-edge computational approaches that generally involve machine learning or computational intelligence techniques, which can effectively perform bioimage and biosignal processing in different clinical areas.



Future Trends And Challenges Of Molecular Imaging And Ai Innovation


Future Trends And Challenges Of Molecular Imaging And Ai Innovation
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Author : Kang-Ping Lin
language : en
Publisher: Springer Nature
Release Date : 2022-02-22

Future Trends And Challenges Of Molecular Imaging And Ai Innovation written by Kang-Ping Lin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-22 with Science categories.


This volumes presents the proceedings of the FASMI 2020 conference, held at Taipei Veterans General Hospital on November 20-22, 2020. It presents contributions on all aspects of molecular imaging, discovered by leading academic scientists and researchers. It also provides a premier interdisciplinary treatment of recent innovations, trend, and concerns as well as practical challenges and solutions in Molecular Imaging and put an emphasis on Artificial Intelligence applied to Imaging Data. FASMI is the annual meeting of the Federation of Asian Societies for Molecular Imaging



Applications Of Parallel Data Processing For Biomedical Imaging


Applications Of Parallel Data Processing For Biomedical Imaging
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Author : Rijwan Khan
language : en
Publisher: Medical Information Science Reference
Release Date : 2024-05-31

Applications Of Parallel Data Processing For Biomedical Imaging written by Rijwan Khan and has been published by Medical Information Science Reference this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-31 with Computers categories.


Despite the remarkable progress witnessed in the last decade in big data utilization and parallel processing techniques, a persistent disparity exists between the capabilities of computer-aided diagnosis systems and the intricacies of practical healthcare scenarios. This disconnection is particularly evident in the complex landscape of artificial intelligence (AI) and IoT innovations within the biomedical realm. The need to bridge this gap and explore the untapped potential in healthcare and biomedical applications has never been more crucial. As we navigate through these challenges, Applications of Parallel Data Processing for Biomedical Imaging offers insights and solutions to reshape the future of biomedical research. The objective of Applications of Parallel Data Processing for Biomedical Imaging is to bring together researchers from both the computer science and biomedical research communities. By showcasing state-of-the-art deep learning and large data analysis technologies, the book provides a platform for the cross-pollination of ideas between AI-based and traditional methodologies. The collaborative effort seeks to have a substantial impact on data mining, AI, computer vision, biomedical research, healthcare engineering, and other related fields. This interdisciplinary approach positions the book as a cornerstone for scholars, professors, and professionals working in software and medical fields, catering to both graduate and undergraduate students eager to explore the evolving landscape of parallel computing, artificial intelligence, and their applications in biomedical research. The topics covered in the book span a diverse range, including heterogeneous computing, biological and molecular computing, AI applications in biomedical imaging, big data processing, and future network architectures for parallel processing. Readers will delve into the frontiers of AI and deep learning in medicine, human biology, and healthcare, exploring machine learning and deep learning-based clinical decision-making systems, biomedical imaging, medical and healthcare education, and more. The book acts as a beacon for those intrigued by the possibilities at the intersection of big data, intelligent IoT, and parallel computing in reshaping the landscape of healthcare, bioinformatics, biomechanics, and biomedical services.



Medical Applications Of Artificial Intelligence


Medical Applications Of Artificial Intelligence
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Author : Arvin Agah
language : en
Publisher: CRC Press
Release Date : 2013-11-06

Medical Applications Of Artificial Intelligence written by Arvin Agah and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-06 with Medical categories.


Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to succeed, medical and computational scientists must dev



Artificial Intelligence In Medical Imaging


Artificial Intelligence In Medical Imaging
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Author : Lia Morra
language : en
Publisher: CRC Press
Release Date : 2019-11-25

Artificial Intelligence In Medical Imaging written by Lia Morra and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-25 with Science categories.


This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed and which failed, from the era of computer aided detection systems on to the current cutting-edge applications in deep learning today, which are starting to exhibit on-par performance with clinical experts. In the last section, the book offers a view on the complexity of the validation of artificial intelligence applications for commercial use, describing the recently introduced concept of software as a medical device, as well as good practices and relevant considerations for training and testing machine learning systems for medical use. Open problematics on the validation for public use of systems which by nature continuously evolve through new data is also explored. The book will be of interest to graduate students in medical physics, biomedical engineering and computer science, in addition to researchers and medical professionals operating in the medical imaging domain, who wish to better understand these technologies and the future of the field. Features: An accessible yet detailed overview of the field Explores a hot and growing topic Provides an interdisciplinary perspective



Handbook Of Artificial Intelligence In Biomedical Engineering


Handbook Of Artificial Intelligence In Biomedical Engineering
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Author : Saravanan Krishnan
language : en
Publisher: CRC Press
Release Date : 2021-03-30

Handbook Of Artificial Intelligence In Biomedical Engineering written by Saravanan Krishnan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-30 with Computers categories.


Handbook of Artificial Intelligence in Biomedical Engineering focuses on recent AI technologies and applications that provide some very promising solutions and enhanced technology in the biomedical field. Recent advancements in computational techniques, such as machine learning, Internet of Things (IoT), and big data, accelerate the deployment of biomedical devices in various healthcare applications. This volume explores how artificial intelligence (AI) can be applied to these expert systems by mimicking the human expert’s knowledge in order to predict and monitor the health status in real time. The accuracy of the AI systems is drastically increasing by using machine learning, digitized medical data acquisition, wireless medical data communication, and computing infrastructure AI approaches, helping to solve complex issues in the biomedical industry and playing a vital role in future healthcare applications. The volume takes a multidisciplinary perspective of employing these new applications in biomedical engineering, exploring the combination of engineering principles with biological knowledge that contributes to the development of revolutionary and life-saving concepts.



Applications Of Artificial Intelligence In Medical Imaging


Applications Of Artificial Intelligence In Medical Imaging
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Author : Abdulhamit Subasi
language : en
Publisher: Academic Press
Release Date : 2022-11-10

Applications Of Artificial Intelligence In Medical Imaging written by Abdulhamit Subasi and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-10 with Science categories.


Applications of Artificial Intelligence in Medical Imaging provides the description of various biomedical image analysis in disease detection using AI that can be used to incorporate knowledge obtained from different medical imaging devices such as CT, X-ray, PET and ultrasound. The book discusses the use of AI for detection of several cancer types, including brain tumor, breast, pancreatic, rectal, lung colon, and skin. In addition, it explains how AI and deep learning techniques can be used to diagnose Alzheimer's, Parkinson's, COVID-19 and mental conditions. This is a valuable resource for clinicians, researchers and healthcare professionals who are interested in learning more about AI and its impact in medical/biomedical image analysis. Discusses new deep learning algorithms for image analysis and how they are used for medical images Provides several examples for each imaging technique, along with their application areas so that readers can rely on them as a clinical decision support system Describes how new AI tools may contribute significantly to the successful enhancement of a single patient's clinical knowledge to improve treatment outcomes