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Author: Abhineet Anand Publisher: ISBN: Category : Computers Languages : en Pages : 0
Book Description
"This book is the culmination of our collaborative efforts, bringing together expertise from various disciplines, including artificial intelligence, computer science, neuroscience, and healthcare. Our shared goal is to address the pressing challenges posed by Alzheimer's disease through innovative AI-driven solutions"--
Author: KHRITISH SWARGIARY Publisher: ERA, US ISBN: Category : Education Languages : en Pages : 158
Book Description
In the field of medical research and technological innovation, few challenges are as profound and pressing as the quest to understand and combat Alzheimer’s Disease. This neurodegenerative disorder, characterized by progressive memory loss and cognitive decline, affects millions of individuals worldwide and poses significant challenges for patients, families, and healthcare systems alike. The search for effective diagnostic tools, prognostic indicators, and therapeutic interventions remains a critical area of scientific inquiry. The emergence of Artificial Intelligence (AI) has heralded a new era of possibilities in healthcare, offering transformative potential for the study and treatment of Alzheimer’s Disease. By leveraging advanced computational techniques, machine learning algorithms, and data analytics, AI holds the promise of revolutionizing our approach to understanding the complexities of this disease. From early diagnosis to personalized treatment and patient monitoring, AI's applications in Alzheimer’s research and care are rapidly expanding, presenting both opportunities and challenges that warrant thorough exploration. This book aims to provide a comprehensive overview of the intersection between AI and Alzheimer’s Disease. It is designed to serve as a valuable resource for researchers, clinicians, policymakers, and students who are engaged in the fields of neurology, artificial intelligence, and healthcare technology. Through a detailed examination of current advancements, practical applications, and future directions, this work seeks to illuminate the transformative impact of AI on Alzheimer’s research and patient care.
Author: Lilhore, Umesh Kumar Publisher: IGI Global ISBN: Category : Medical Languages : en Pages : 477
Book Description
Alzheimer's disease (AD) poses a significant global health challenge, with an estimated 50 million people affected worldwide and no known cure. Traditional methods of diagnosis and prediction often rely on subjective assessments. They are limited in detecting the disease early, leading to delayed intervention and poorer patient outcomes. Additionally, the complexity of AD, with its multifactorial etiology and diverse clinical manifestations, requires a multidisciplinary approach for effective management. AI-Driven Alzheimer's Disease Detection and Prediction offers a groundbreaking solution by leveraging advanced artificial intelligence (AI) techniques to enhance early diagnosis and prediction of AD. This edited book provides a comprehensive overview of state-of-the-art research, methodologies, and applications at the intersection of AI and AD detection. By bridging the gap between traditional diagnostic methods and cutting-edge technology, this book facilitates knowledge exchange, fosters interdisciplinary collaboration, and contributes to innovative solutions for AD management.
Author: Adam Bohr Publisher: Academic Press ISBN: 0128184396 Category : Computers Languages : en Pages : 385
Book Description
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data
Author: Miltiadis Lytras Publisher: Academic Press ISBN: 0128220627 Category : Medical Languages : en Pages : 292
Book Description
Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved in healthcare as they strive to enhance the value added of healthcare and develop more sustainable healthcare systems. It brings together insights from emerging sophisticated information and communication technologies such as big data analytics, artificial intelligence, machine learning, data science, medical intelligence, and, by dwelling on their current and prospective applications, highlights managerial and policymaking challenges they may generate. The book is split into five sections: big data infrastructure, framework and design for smart healthcare; signal processing techniques for smart healthcare applications; business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcare; emerging tools and techniques for smart healthcare; and challenges (security, privacy, and policy) in big data for smart healthcare. The content is carefully developed to be understandable to different members of healthcare chain to leverage collaborations with researchers and industry. Presents a holistic discussion on the new landscape of data driven medical technologies including Big Data, Analytics, Artificial Intelligence, Machine Learning, and Precision Medicine Discusses such technologies with case study driven approach with reference to real world application and systems, to make easier the understanding to the reader not familiar with them Encompasses an international collaboration perspective, providing understandable knowledge to professionals involved with healthcare to leverage productive partnerships with technology developers
Author: Islem Rekik Publisher: Springer ISBN: 9783030322809 Category : Computers Languages : en Pages : 178
Book Description
This book constitutes the proceedings of the Second International Workshop on Predictive Intelligence in Medicine, PRIME 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. The 18 papers presented in this volume were carefully reviewed and selected for inclusion in this book. The contributions describe new cutting-edge predictive models and methods that solve challenging problems in the medical field for a high-precision predictive medicine.
Author: Colin R Martin Publisher: Academic Press ISBN: 0128158557 Category : Medical Languages : en Pages : 912
Book Description
Diagnosis and Management in Dementia: The Neuroscience of Dementia, Volume 1 consolidates different fields of dementia into a single book, covering a range of subjects, including Alzheimer’s disease, Lewy body dementia, mixed dementia, vascular dementia, physical activity, risk factors, mortality, biomarkers, SPECT, CT, MRI, questionnaires, nutrition, sleep, delirium, hearing loss, agitation, aggression, delusions, anxiety, depression, hallucinations, psychosis, senile plaques, tau and amyloid-beta, neuroinflammation, molecular biology, and more. With an impact on millions globally, and billions of research dollars being invested in dementia research, this book will stimulate research in the area and inform researchers. Offers comprehensive coverage of a broad range of topics related to dementia Serves as a foundational collection for neuroscientists and neurologists on the biology of dementia and brain dysfunction Contains in each chapter an abstract, key facts, mini dictionary of terms, and summary points to aid in understanding Provides unique sections on specific subareas, intellectual components, and knowledge-based niches that will help readers navigate key areas for research and further clinical recommendations Features preclinical and clinical studies to help researchers map out key areas for research and further clinical recommendations Serves as a "one-stop" source for everything you need to know about dementia
Author: Manish Prateek Publisher: Springer Nature ISBN: 9813340878 Category : Artificial intelligence Languages : en Pages : 813
Book Description
This book is a compilation of peer-reviewed papers presented at the International Conference on Machine Intelligence and Data Science Applications, organized by the School of Computer Science, University of Petroleum & Energy Studies, Dehradun, on September 4 and 5, 2020. The book starts by addressing the algorithmic aspect of machine intelligence which includes the framework and optimization of various states of algorithms. Variety of papers related to wide applications in various fields like image processing, natural language processing, computer vision, sentiment analysis, and speech and gesture analysis have been included with upfront details. The book concludes with interdisciplinary applications like legal, health care, smart society, cyber physical system and smart agriculture. The book is a good reference for computer science engineers, lecturers/researchers in machine intelligence discipline and engineering graduates.
Author: D.J. Hemanth Publisher: IOS Press ISBN: 1614998221 Category : Computers Languages : en Pages : 284
Book Description
Deep learning and image processing are two areas of great interest to academics and industry professionals alike. The areas of application of these two disciplines range widely, encompassing fields such as medicine, robotics, and security and surveillance. The aim of this book, ‘Deep Learning for Image Processing Applications’, is to offer concepts from these two areas in the same platform, and the book brings together the shared ideas of professionals from academia and research about problems and solutions relating to the multifaceted aspects of the two disciplines. The first chapter provides an introduction to deep learning, and serves as the basis for much of what follows in the subsequent chapters, which cover subjects including: the application of deep neural networks for image classification; hand gesture recognition in robotics; deep learning techniques for image retrieval; disease detection using deep learning techniques; and the comparative analysis of deep data and big data. The book will be of interest to all those whose work involves the use of deep learning and image processing techniques.
Author: Anitha S. Pillai Publisher: Academic Press ISBN: 0323886264 Category : Science Languages : en Pages : 356
Book Description
Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence focuses on how the neurosciences can benefit from advances in AI, especially in areas such as medical image analysis for the improved diagnosis of Alzheimer’s disease, early detection of acute neurologic events, prediction of stroke, medical image segmentation for quantitative evaluation of neuroanatomy and vasculature, diagnosis of Alzheimer’s Disease, autism spectrum disorder, and other key neurological disorders. Chapters also focus on how AI can help in predicting stroke recovery, and the use of Machine Learning and AI in personalizing stroke rehabilitation therapy. Other sections delve into Epilepsy and the use of Machine Learning techniques to detect epileptogenic lesions on MRIs and how to understand neural networks. Provides readers with an understanding on the key applications of artificial intelligence and machine learning in the diagnosis and treatment of the most important neurological disorders Integrates recent advancements of artificial intelligence and machine learning to the evaluation of large amounts of clinical data for the early detection of disorders such as Alzheimer’s Disease, autism spectrum disorder, Multiple Sclerosis, headache disorder, Epilepsy, and stroke Provides readers with illustrative examples of how artificial intelligence can be applied to outcome prediction, neurorehabilitation and clinical exams, including a wide range of case studies in predicting and classifying neurological disorders
Author: Abhineet Anand
Author: Abhineet Anand
Author: KHRITISH SWARGIARY
Author: Lilhore, Umesh Kumar
Author: Adam Bohr
Author: Miltiadis Lytras
Author: Islem Rekik
Author: Colin R Martin
Author: Manish Prateek
Author: D.J. Hemanth
Author: Anitha S. Pillai