Machine Learning And Decision Support In Stroke

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Machine Learning And Decision Support In Stroke

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Author : Fabien Scalzo
language : en
Publisher: Frontiers Media SA
Release Date : 2020-07-09

Machine Learning And Decision Support In Stroke written by Fabien Scalzo 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 2020-07-09 with categories.

Decision Support In Clinical Practice For Stroke Clinician Experiences And Expectations

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Author : Andrew Bivard
language : en
Publisher: Frontiers Media SA
Release Date : 2021-07-01

Decision Support In Clinical Practice For Stroke Clinician Experiences And Expectations written by Andrew Bivard 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 2021-07-01 with Medical categories.

Machine Learning In Data Analysis For Stroke Endovascular Therapy

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Author : Benjamin Yim
language : en
Publisher: Frontiers Media SA
Release Date : 2023-09-05

Machine Learning In Data Analysis For Stroke Endovascular Therapy written by Benjamin Yim 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 2023-09-05 with Medical categories.

With an estimated global incidence of 11 million patients per year, research involving ischemic stroke requires the collection and analysis of massive data sets affected by innumerable variables. Landmark studies that have historically shaped the foundation of our understanding of ischemic stroke and the development of management protocols have been derived from only a miniscule fraction of a percent of the entire population due to feasibility and capability. Machine learning provides an opportunity to capture data from an extraordinarily larger cohort size, which can be applied to training models to formulate algorithms to forecast outcomes with unparalleled accuracy and efficiency. The paradigm-shifting integration of machine learning in other industries, i.e. robotics, finance, and marketing, foreshadows its inevitable application to large population-based clinical research and practice. While prior multi-center studies have relied heavily on catalogued datasets requiring substantial manpower, the recent development of modern statistical methods can potentially expand the available quantity and quality of clinical data. In conjunction with data mining, machine learning has allowed automated extraction of clinical information from imaging, surgical videos, and electronic medical records to identify previously unseen patterns and create prediction models. Recently, it’s use in real-time detection of large vessel occlusion has streamlined health care delivery to a level of efficiency previously unmatched. The application of machine learning in ischemic stroke research – data acquisition, image evaluation, and prediction models – has the potential to reduce human error and increase reproducibility, accuracy, and precision with an unprecedented degree of power. However, one of the challenges with this integration remains the methods in which machine learning is utilized. Given the novelty of machine learning in clinical research, there remains significant variations in the application of machine learning tools and algorithms. The focus of the research topic is to provide a platform to compare the merits of various learning approaches – supervised, semi-supervised, unsupervised, self-learning – and the performances of various models.

Deep Learning In Personalized Healthcare And Decision Support

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Author : Harish Garg
language : en
Publisher: Elsevier
Release Date : 2023-07-20

Deep Learning In Personalized Healthcare And Decision Support written by Harish Garg and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-20 with Science categories.

Deep Learning in Personalized Healthcare and Decision Support discusses the potential of deep learning technologies in the healthcare sector. The book covers the application of deep learning tools and techniques in diverse areas of healthcare, such as medical image classification, telemedicine, clinical decision support system, clinical trials, electronic health records, precision medication, Parkinson disease detection, genomics, and drug discovery. In addition, it discusses the use of DL for fraud detection and internet of things. This is a valuable resource for researchers, graduate students and healthcare professionals who are interested in learning more about deep learning applied to the healthcare sector. Although there is an increasing interest by clinicians and healthcare workers, they still lack enough knowledge to efficiently choose and make use of technologies currently available. This book fills that knowledge gap by bringing together experts from technology and clinical fields to cover the topics in depth. - Discusses the application of deep learning in several areas of healthcare, including clinical trials, telemedicine and health records management - Brings together experts in the intersection of deep learning, medicine, healthcare and programming to cover topics in an interdisciplinary way - Uncovers the stakes and possibilities involved in realizing personalized healthcare services through efficient and effective deep learning technologies

Challenges In Information Communication And Computing Technology

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Author : V. Sharmila
language : en
Publisher: CRC Press
Release Date : 2024-12-10

Challenges In Information Communication And Computing Technology written by V. Sharmila and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-10 with Technology & Engineering categories.

This book explores the critical challenges and emerging trends in Information, Communication, and Computing Technology (ICCT). It provides a comprehensive overview of the key issues facing these rapidly evolving fields, from data security and privacy to advancements in artificial intelligence, communication networks, and quantum computing. Through in-depth analysis and expert perspectives, this volume aims to shed light on the complexities of ICCT and offer innovative solutions for researchers, practitioners, and students. Building on its exploration of challenges in ICCT, this book delves into several core areas. These include the development and deployment of secure and efficient communication networks, the ethical implications and technical hurdles of artificial intelligence and machine learning, and the promise and complexity of quantum computing. The book also addresses the management of big data, highlighting both its potential and the challenges of ensuring data privacy and security. Additionally, it examines the role of sustainability in computing, advocating for greener technologies and practices. The findings presented in this volume emphasize the need for interdisciplinary approaches and innovative thinking to address these challenges, offering insights that are both practical and forward-looking. This book is intended for a diverse audience that includes researchers, practitioners, and students in the fields of Information, Communication, and Computing Technology (ICCT). It is particularly valuable for academics and professionals seeking to deepen their understanding of current challenges and emerging trends in these areas. Additionally, policymakers, industry leaders, and technologists will find the book's insights useful for informing decisions and strategies in the development and implementation of advanced technologies. Whether you are a seasoned expert or a newcomer to the field, this book provides valuable perspectives that can enhance your knowledge and contribute to your work in ICCT. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons [Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND)] 4.0 license.

Advancing Medical Research Through Neuroscience

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Author : Mathivanan, Sandeep Kumar
language : en
Publisher: IGI Global
Release Date : 2025-02-26

Advancing Medical Research Through Neuroscience written by Mathivanan, Sandeep Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-26 with Medical categories.

In the field of medical research, scholars must leverage the latest advancements in neuroscience to revolutionize healthcare outcomes. This book offers a compelling exploration into the dynamic intersection of neuroscience and medical science, presenting a comprehensive guide to the latest advancements shaping healthcare. Delving deep into the intricate workings of the brain and nervous system, this book provides a foundational understanding of neuroscience principles, setting the stage for groundbreaking insights into medical breakthroughs. From unraveling the mysteries of neurological disorders to harnessing the brain's remarkable ability to heal itself through neuroplasticity, each chapter within Advancing Medical Research Through Neuroscience explores specific aspect of neuroscience's impact on medical research. Cutting-edge technologies such as functional MRI and optogenetics are examined alongside innovative treatment strategies for conditions ranging from addiction to neurodegenerative diseases like Alzheimer's and Parkinson's. Whether you're a student, researcher, or healthcare professional, this book serves as an indispensable resource, inspiring collaboration and innovation to drive progress in healthcare and improve patient outcomes.

Machine Learning And Deep Learning In Neuroimaging Data Analysis

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Author : Anitha S. Pillai
language : en
Publisher: CRC Press
Release Date : 2024-02-15

Machine Learning And Deep Learning In Neuroimaging Data Analysis written by Anitha S. Pillai and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-15 with Computers categories.

Machine learning (ML) and deep learning (DL) have become essential tools in healthcare. They are capable of processing enormous amounts of data to find patterns and are also adopted into methods that manage and make sense of healthcare data, either electronic healthcare records or medical imagery. This book explores how ML/DL can assist neurologists in identifying, classifying or predicting neurological problems that require neuroimaging. With the ability to model high-dimensional datasets, supervised learning algorithms can help in relating brain images to behavioral or clinical observations and unsupervised learning can uncover hidden structures/patterns in images. Bringing together artificial intelligence (AI) experts as well as medical practitioners, these chapters cover the majority of neuro problems that use neuroimaging for diagnosis, along with case studies and directions for future research.

Advances In Communication And Applications

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Author : N. R. Shetty
language : en
Publisher: Springer Nature
Release Date : 2024-01-06

Advances In Communication And Applications written by N. R. Shetty and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-06 with Technology & Engineering categories.

This book presents the proceedings of the International Conference on Emerging Research in Computing, Information, Communication and Applications (ERCICA) 2023. The conference provides an interdisciplinary forum for researchers, professional engineers and scientists, educators and technologists to discuss, debate and promote research and technology in the upcoming areas of computing, information, communication and their applications. Some of the topics include the Internet of Things (IoT), wireless communications, image and video processing, parallel and distributed computing, and smart grid applications, among others. The book discusses these emerging research areas, providing a valuable resource for researchers and practicing engineers alike.

Artificial Intelligence In Neurological Disorders

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Author : Rishabha Malviya
language : en
Publisher: John Wiley & Sons
Release Date : 2025-08-04

Artificial Intelligence In Neurological Disorders written by Rishabha Malviya 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 2025-08-04 with Computers categories.

The book gives invaluable insights into how artificial intelligence is revolutionizing the management and treatment of neurological disorders, empowering you to stay ahead in the rapidly evolving landscape of healthcare. Embark on a groundbreaking exploration of the intersection between cutting-edge technology and the intricate complexities of neurological disorders. Artificial Intelligence in Neurological Disorders: Management, Diagnosis and Treatment comprehensively introduces how artificial intelligence is becoming a vital ally in neurology, offering unprecedented advancements in management, diagnosis, and treatment. As the digital age converges with medical expertise, this book unveils a comprehensive roadmap for leveraging artificial intelligence to revolutionize neurological healthcare. Delve into the core principles that underpin AI applications in the field by exploring intricate algorithms that enhance the precision of diagnosis and how machine learning not only refines the understanding of neurological disorders but also paves the way for personalized treatment strategies tailored to individual patient needs. With compelling case studies and real-world examples, the realms of neuroscience and artificial intelligence converge, illustrating the symbiotic relationship that holds the promise of transforming patient care. Readers of this book will find it: Provides future perspectives on advancing artificial intelligence applications in neurological disorders; Focuses on the role of AI in diagnostics, delving into how advanced algorithms and machine learning techniques contribute to more accurate and timely diagnosis of neurological disorders; Emphasizes practical integration of AI tools into clinical practice, offering insights into how healthcare professionals can leverage AI technology for more effective patient care; Recognizes the interdisciplinary nature of neurology and AI, bridging the gap between these fields, making it accessible to healthcare professionals, researchers, and technologists; Addresses the ethical implications of AI in healthcare, exploring issues such as data privacy, bias, and the responsible deployment of AI technologies in the neurological domain. Audience Researchers, scientists, industrialists, faculty members, healthcare professionals, hospital management, biomedical industrialists, engineers, and IT professionals interested in studying the intersection of AI and neurology.

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