Download Full eBooks in PDF
The Application Of Artificial Intelligence In Diagnosis And Intervention Of Alzheimer S Disease Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of The Application Of Artificial Intelligence In Diagnosis And Intervention Of Alzheimer S Disease book. This book definitely worth reading, it is an incredibly well-written.
Author : Peng Xu,Qi Yang,Jing Jin,Xiuqin Jia,Zehong Jimmy Cao
Publisher : Frontiers Media SA
Page : 162 pages
File Size : 43,9 Mb
Release : 2022-11-15
Category : Science
ISBN : 9782832505755
Author : Adam Bohr,Kaveh Memarzadeh
Publisher : Academic Press
Page : 385 pages
File Size : 53,5 Mb
Release : 2020-06-21
Category : Computers
ISBN : 9780128184394
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 : Loveleen Gaur
Publisher : Springer Nature
Page : 184 pages
File Size : 46,9 Mb
Release : 2024-07-01
Category : Electronic
ISBN : 9783031531484
Author : K. G. Srinivasa,Siddesh G. M.,S. R. Mani Sekhar
Publisher : Springer Nature
Page : 332 pages
File Size : 48,5 Mb
Release : 2021-05-20
Category : Technology & Engineering
ISBN : 9789811604157
This book discusses the advancements in artificial intelligent techniques used in the well-being of human healthcare. It details the techniques used in collection, storage and analysis of data and their usage in different healthcare solutions. It also discusses the techniques of predictive analysis in early diagnosis of critical diseases. The edited book is divided into four parts – part A discusses introduction to artificial intelligence and machine learning in healthcare; part B highlights different analytical techniques used in healthcare; part C provides various security and privacy mechanisms used in healthcare; and finally, part D exemplifies different tools used in visualization and data analytics.
Author : Anonim
Publisher : Unknown
Page : 0 pages
File Size : 40,5 Mb
Release : 2024
Category : Electronic
ISBN : 9798369336052
Author : Jadhav, Dipti,Chavan, Pallavi Vijay,Chaudhari, Sangita,Williams, Idongesit
Publisher : IGI Global
Page : 431 pages
File Size : 51,5 Mb
Release : 2024-02-14
Category : Medical
ISBN : 9798369310915
Cognitive disorders are a growing concern, affecting individuals across the age spectrum and society. These disorders can profoundly disrupt daily life, and their timely diagnosis is crucial for effective intervention and care. As the prevalence of cognitive disorders continues to rise, the need for precise and early diagnosis has never been more pressing. Intelligent Solutions for Cognitive Disorders is a research-based book which delves into the intersection of medical science and technology, exploring the latest advancements in cognitive disorder diagnosis and treatment. This book assembles a multidisciplinary team of experts, including researchers, clinicians, and technologists, to address this challenge head-on. This book commences with an in-depth introduction to cognitive disorders, providing a solid foundation for readers of all backgrounds. It then navigates the role of intelligent systems in cognitive healthcare, unveiling the potential of artificial intelligence, machine learning, and deep learning techniques. The book highlights how these intelligent systems can enable the early and accurate detection of cognitive disorders, a pivotal factor in improving patients' quality of life. This book is an invaluable resource for technologists, researchers, linguists, data scientists, healthcare practitioners, medical professionals, and students seeking a comprehensive understanding of cognitive disorders and the role of intelligent technologies in their diagnosis and care.
Author : K. Gayathri Devi,Kishore Balasubramanian,Le Anh Ngoc
Publisher : CRC Press
Page : 351 pages
File Size : 40,7 Mb
Release : 2022-05-11
Category : Technology & Engineering
ISBN : 9781000583366
The application of machine learning is growing exponentially into every branch of business and science, including medical science. This book presents the integration of machine learning (ML) and deep learning (DL) algorithms that can be applied in the healthcare sector to reduce the time required by doctors, radiologists, and other medical professionals for analyzing, predicting, and diagnosing the conditions with accurate results. The book offers important key aspects in the development and implementation of ML and DL approaches toward developing prediction tools and models and improving medical diagnosis. The contributors explore the recent trends, innovations, challenges, and solutions, as well as case studies of the applications of ML and DL in intelligent system-based disease diagnosis. The chapters also highlight the basics and the need for applying mathematical aspects with reference to the development of new medical models. Authors also explore ML and DL in relation to artificial intelligence (AI) prediction tools, the discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, and pattern recognition approaches to functional magnetic resonance imaging images. This book is for students and researchers of computer science and engineering, electronics and communication engineering, and information technology; for biomedical engineering researchers, academicians, and educators; and for students and professionals in other areas of the healthcare sector. Presents key aspects in the development and the implementation of ML and DL approaches toward developing prediction tools, models, and improving medical diagnosis Discusses the recent trends, innovations, challenges, solutions, and applications of intelligent system-based disease diagnosis Examines DL theories, models, and tools to enhance health information systems Explores ML and DL in relation to AI prediction tools, discovery of drugs, neuroscience, and diagnosis in multiple imaging modalities Dr. K. Gayathri Devi is a Professor at the Department of Electronics and Communication Engineering, Dr. N.G.P Institute of Technology, Tamil Nadu, India. Dr. Kishore Balasubramanian is an Assistant Professor (Senior Scale) at the Department of EEE at Dr. Mahalingam College of Engineering & Technology, Tamil Nadu, India. Dr. Le Anh Ngoc is a Director of Swinburne Innovation Space and Professor in Swinburne University of Technology (Vietnam).
Author : Erik R. Ranschaert,Sergey Morozov,Paul R. Algra
Publisher : Springer
Page : 373 pages
File Size : 42,7 Mb
Release : 2019-01-29
Category : Medical
ISBN : 9783319948782
This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.
Author : Adwitiya Sinha,Megha Rathi
Publisher : CRC Press
Page : 332 pages
File Size : 52,5 Mb
Release : 2019-07-24
Category : Computers
ISBN : 9780429670282
About the Book The book provides details of applying intelligent mining techniques for extracting and pre-processing medical data from various sources, for application-based healthcare research. Moreover, different datasets are used, thereby exploring real-world case studies related to medical informatics. This book would provide insight to the learners about Machine Learning, Data Analytics, and Sustainable Computing. Salient Features of the Book Exhaustive coverage of Data Analysis using R Real-life healthcare models for: Visually Impaired Disease Diagnosis and Treatment options Applications of Big Data and Deep Learning in Healthcare Drug Discovery Complete guide to learn the knowledge discovery process, build versatile real life healthcare applications Compare and analyze recent healthcare technologies and trends Target Audience This book is mainly targeted at researchers, undergraduate, postgraduate students, academicians, and scholars working in the area of data science and its application to health sciences. Also, the book is beneficial for engineers who are engaged in developing actual healthcare solutions.
Author : World Health Organization
Publisher : World Health Organization
Page : 233 pages
File Size : 52,6 Mb
Release : 2006
Category : Medical
ISBN : 9789241563369
Although there are several gaps in understanding the many issues related to neurological disorders, we know enough to be able to shape effective policy responses to some of the most common. This book describes and discusses the increasing public health impact of common neurological disorders such as dementia, epilepsy, headache disorders, multiple sclerosis, neuroinfections, neurological disorders associated with malnutrition, pain associated with neurological disorders, Parkinson's disease, stroke and traumatic brain injuries. It provides information and advice on public health interventions that may reduce their occurrence and consequences, and offers health professionals and planners the opportunity to assess the burden caused by these disorders. The clear message that emerges is that unless immediate action is taken globally, the neurological burden is likely to become an increasingly serious and unmanageable.
Author : Mullaicharam Bhupathyraaj
Publisher : Springer Nature
Page : 271 pages
File Size : 49,9 Mb
Release : 2024-07-01
Category : Electronic
ISBN : 9789819725779
Author : Andrzej Grzybowski
Publisher : Springer Nature
Page : 280 pages
File Size : 50,8 Mb
Release : 2021-10-13
Category : Medical
ISBN : 9783030786014
This book provides a wide-ranging overview of artificial intelligence (AI), machine learning (ML) and deep learning (DL) algorithms in ophthalmology. Expertly written chapters examine AI in age-related macular degeneration, glaucoma, retinopathy of prematurity and diabetic retinopathy screening. AI perspectives, systems and limitations are all carefully assessed throughout the book as well as the technical aspects of DL systems for retinal diseases including the application of Google DeepMind, the Singapore algorithm, and the Johns Hopkins algorithm. Artificial Intelligence in Ophthalmology meets the need for a resource that reviews the benefits and pitfalls of AI, ML and DL in ophthalmology. Ophthalmologists, optometrists, eye-care workers, neurologists, cardiologists, internal medicine specialists, AI engineers and IT specialists with an interest in how AI can help with early diagnosis and monitoring treatment in ophthalmic patients will find this book to be an indispensable guide to an evolving area of healthcare technology.
Author : Hemanth D. Jude
Publisher : Academic Press
Page : 320 pages
File Size : 43,9 Mb
Release : 2021-03-30
Category : Science
ISBN : 9780128222720
Handbook of Decision Support Systems for Neurological Disorders provides readers with complete coverage of advanced computer-aided diagnosis systems for neurological disorders. While computer-aided decision support systems for different medical imaging modalities are available, this is the first book to solely concentrate on decision support systems for neurological disorders. Due to the increase in the prevalence of diseases such as Alzheimer, Parkinson’s and Dementia, this book will have significant importance in the medical field. Topics discussed include recent computational approaches, different types of neurological disorders, deep convolution neural networks, generative adversarial networks, auto encoders, recurrent neural networks, and modified/hybrid artificial neural networks. Includes applications of computer intelligence and decision support systems for the diagnosis and analysis of a variety of neurological disorders Presents in-depth, technical coverage of computer-aided systems for tumor image classification, Alzheimer’s disease detection, dementia detection using deep belief neural networks, and morphological approaches for stroke detection Covers disease diagnosis for cerebral palsy using auto-encoder approaches, contrast enhancement for performance enhanced diagnosis systems, autism detection using fuzzy logic systems, and autism detection using generative adversarial networks Written by engineers to help engineers, computer scientists, researchers and clinicians understand the technology and applications of decision support systems for neurological disorders
Author : Kohei Arai
Publisher : Springer Nature
Page : 648 pages
File Size : 49,8 Mb
Release : 2023-11-08
Category : Technology & Engineering
ISBN : 9783031474576
This book is a collection of thoroughly well-researched studies presented at the Eighth Future Technologies Conference. This annual conference aims to seek submissions from the wide arena of studies like Computing, Communication, Machine Vision, Artificial Intelligence, Ambient Intelligence, Security, and e-Learning. With an impressive 490 paper submissions, FTC emerged as a hybrid event of unparalleled success, where visionary minds explored groundbreaking solutions to the most pressing challenges across diverse fields. These groundbreaking findings open a window for vital conversation on information technologies in our community especially to foster future collaboration with one another. We hope that the readers find this book interesting and inspiring and render their enthusiastic support toward it.
Author : Ajith Abraham,Sujata Dash,Subhendu Kumar Pani,Laura García-Hernández
Publisher : Academic Press
Page : 434 pages
File Size : 42,5 Mb
Release : 2022-09-23
Category : Medical
ISBN : 9780323902786
Artificial Intelligence for Neurological Disorders provides a comprehensive resource of state-of-the-art approaches for AI, big data analytics and machine learning-based neurological research. The book discusses many machine learning techniques to detect neurological diseases at the cellular level, as well as other applications such as image segmentation, classification and image indexing, neural networks and image processing methods. Chapters include AI techniques for the early detection of neurological disease and deep learning applications using brain imaging methods like EEG, MEG, fMRI, fNIRS and PET for seizure prediction or neuromuscular rehabilitation. The goal of this book is to provide readers with broad coverage of these methods to encourage an even wider adoption of AI, Machine Learning and Big Data Analytics for problem-solving and stimulating neurological research and therapy advances. Discusses various AI and ML methods to apply for neurological research Explores Deep Learning techniques for brain MRI images Covers AI techniques for the early detection of neurological diseases and seizure prediction Examines cognitive therapies using AI and Deep Learning methods