Deep Generative Models for Integrative Analysis of Alzheimer's Biomarkers PDF Download
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Author: Kumar, Abhishek
Publisher: IGI Global
ISBN:
Category : Medical
Languages : en
Pages : 536
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Book Description
The integration of generative AI and deep learning techniques for Alzheimer's disease detection significantly impacts the research community by advancing diagnostic accuracy and providing a comprehensive understanding of the disease. By combining multiple data modalities, including imaging, genetics, and clinical data, researchers can improve diagnostic precision and develop personalized treatment strategies. Generative AI facilitates efficient data utilization through dataset augmentation, fostering innovation and collaboration across interdisciplinary fields. These methodologies forward the exploration of new diagnostic tools while expediting their application in clinical practice, benefiting patients through early detection and intervention. The incorporation of generative AI may enhance research capabilities, promote collaboration, and improve Alzheimer's disease management and patient outcomes. Deep Generative Models for Integrative Analysis of Alzheimer's Biomarkers explores the integration of deep generative models in disease diagnosis, biomarking, and prediction. It examines the use of tools like data analysis, natural language processing, and machine learning for effective Alzheimer’s research. This book covers topics such as data analysis, biomedicine, and machine learning, and is a useful resource for computer engineers, biologists, scientists, medical professionals, healthcare workers, academicians, and researchers.
Author: Kumar, Abhishek
Publisher: IGI Global
ISBN:
Category : Medical
Languages : en
Pages : 536
Get Book Here
Book Description
The integration of generative AI and deep learning techniques for Alzheimer's disease detection significantly impacts the research community by advancing diagnostic accuracy and providing a comprehensive understanding of the disease. By combining multiple data modalities, including imaging, genetics, and clinical data, researchers can improve diagnostic precision and develop personalized treatment strategies. Generative AI facilitates efficient data utilization through dataset augmentation, fostering innovation and collaboration across interdisciplinary fields. These methodologies forward the exploration of new diagnostic tools while expediting their application in clinical practice, benefiting patients through early detection and intervention. The incorporation of generative AI may enhance research capabilities, promote collaboration, and improve Alzheimer's disease management and patient outcomes. Deep Generative Models for Integrative Analysis of Alzheimer's Biomarkers explores the integration of deep generative models in disease diagnosis, biomarking, and prediction. It examines the use of tools like data analysis, natural language processing, and machine learning for effective Alzheimer’s research. This book covers topics such as data analysis, biomedicine, and machine learning, and is a useful resource for computer engineers, biologists, scientists, medical professionals, healthcare workers, academicians, and researchers.
Author: Islem Rekik
Publisher:
ISBN: 9783030003210
Category : Artificial intelligence
Languages : en
Pages : 174
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Book Description
This book constitutes the refereed proceedings of the First International Workshop on PRedictive Intelligence in MEdicine, PRIME 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 20 full papers presented were carefully reviewed and selected from 23 submissions. The main aim of the workshop is to propel the advent of predictive models in a broad sense, with application to medical data. Particularly, the workshop will admit papers describing new cutting-edge predictive models and methods that solve challenging problems in the medical field.
Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385
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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: Simon D. Shorvon
Publisher: Springer Science & Business Media
ISBN: 1461525462
Category : Medical
Languages : en
Pages : 297
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Book Description
It was only in 1980 that the first recognisable magnetic resonance images of the human brain were published, by Moore and Holland from Nottingham University in England. There then followed a number of clinical trials of brain imaging, the most notable from the Hammersmith Hospital in London using a system designed by EMI, the original manufacturers of the first CT machines. A true revolution in medicine has ensued; in only a few years there are thousands of scanning units, and magnetic resonance imaging (MRI) has assumed a central importance in medical investigation. It is an extraordinary fact that within a few years of development, the esoteric physics of nuclear spin, angular momentum, and magnetic vector precession were harnessed to provide exquisite images of living anatomy; modem science has no greater tribute. That indisputable king of neurology and the oldest of recorded conditions, epilepsy, has not been untouched by the new technology; indeed, it is our view that the introduction of MRI of electroencephalography (EEG) in the late has been as important to epilepsy as was that 1930s. Now, for the first time, the structural and aetiological basis of the condition is susceptible to thorough investigation, and MRI can provide structural detail to parallel the functional detail of EEG. MRI has the same potential as had EEG over 50 years ago, to provide a new level of understanding of the basic mechanisms, the clinical features and the treatment of epilepsy.
Author: Erik R. Ranschaert
Publisher: Springer
ISBN: 3319948784
Category : Medical
Languages : en
Pages : 369
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Book Description
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: Jeffrey Cummings
Publisher: Cambridge University Press
ISBN: 1108838669
Category : Business & Economics
Languages : en
Pages : 575
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Book Description
Provides a definitive overview of the complex ecosystem facilitating Alzheimer's Disease drug research and development. Demonstrates a drug's journey from in the lab, clinical trial testing, regulatory review, and marketing by pharmaceutical companies. Details the use of artificial intelligence, clinical trial management, and financing models.
Author: Gérard Emilien
Publisher: Birkhäuser
ISBN: 3034878427
Category : Medical
Languages : en
Pages : 299
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Book Description
Alzheimer disease (AD) has become the most common form of dementia in industrialized countries and represents an increasing burden at the economic, social and medical level. In discussing both the biological aspects of AD as well as the cognitive functions involved, Alzheimer Disease - Neuropsychology and Pharmacology presents a comprehensive picture of the pathology and approaches to diagnosis and treatment. Basic research including animal models, molecular and genetic aspects is also taken into consideration. In part I, the biological correlates of AD are discussed. In part II the neuropsychological aspects such as cognitive impairment, loss of functional autonomy and emergence of neuropsychiatric disturbances of AD are outlined. In part III, strategies for effective treatment and prevention of AD are discussed. This book will be a useful source of information for clinicians as well as researchers in the area of neuropharmacology.
Author: Mousumi Debnath
Publisher: Springer Science & Business Media
ISBN: 9048132614
Category : Medical
Languages : en
Pages : 527
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Book Description
A rapid development in diverse areas of molecular biology and genetic engineering resulted in emergence of variety of tools. These tools are not only applicable to basic researches being carried out world over, but also exploited for precise detection of abnormal conditions in plants, animals and human body. Although a basic researcher is well versed with few techniques used by him/her in the laboratory, they may not be well acquainted with methodologies, which can be used to work out some of their own research problems. The picture is more blurred when the molecular diagnostic tools are to be used by physicians, scientists and technicians working in diagnostic laboratories in hospitals, industry and academic institutions. Since many of them are not trained in basics of these methods, they come across several gray areas in understanding of these tools. The accurate application of molecular diagnostic tools demands in depth understanding of the methodology for precise detection of the abnormal condition of living body. To meet the requirements of a good book on molecular diagnostics of students, physicians, scientists working in agricultural, veterinary, medical and pharmaceutical sciences, it needs to expose the reader lucidly to: Give basic science behind commonly used tools in diagnostics Expose the readers to detailed applications of these tools and Make them aware the availability of such diagnostic tools The book will attract additional audience of pathologists, medical microbiologists, pharmaceutical sciences, agricultural scientists and veterinary doctors if the following topics are incorporated at appropriate places in Unit II or separately as a part of Unit-III in the book. Molecular diagnosis of diseases in agricultural crops Molecular diagnosis of veterinary diseases. Molecular epidemiology, which helps to differentiate various epidemic strains and sources of disease outbreaks. Even in different units of the same hospital, the infections could be by different strains of the same species and the information becomes valuable for infection control strategies. Drug resistance is a growing problem for bacterial, fungal and parasitic microbes and the molecular biology tools can help to detect the drug resistance genes without the cultivation and in vitro sensitivity testing. Molecular diagnostics offers faster help in the selection of the proper antibiotic for the treatment of tuberculosis, which is a major problem of the in the developing world. The conventional culture and drug sensitivity testing of tuberculosis bacilli is laborious and time consuming, whereas molecular diagnosis offers rapid drug resistant gene detection even from direct clinical samples. The same approach for HIV, malaria and many more diseases needs to be considered. Molecular diagnostics in the detection of diseases during foetal life is an upcoming area in the foetal medicine in case of genetic abnormalities and infectious like TORCH complex etc. The book will be equally useful to students, scientists and professionals working in the field of molecular diagnostics.
Author: Dennis J. Selkoe
Publisher: Cold Spring Harbor Perspective
ISBN: 9781936113446
Category : Medical
Languages : en
Pages : 0
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Book Description
Alzheimer disease causes the gradual deterioration of cognitive function, including severe memory loss and impairments in abstraction and reasoning. Understanding the complex changes that occur in the brain as the disease progressesincluding the accumulation of amyloid plaques and neurofibrillary tanglesis critical for the development of successful therapeutic approaches. Written and edited by leading experts in the field, this collection from Cold Spring Harbor Perspectives in Medicine includes contributions covering all aspects of Alzheimer disease, from our current molecular understanding to therapeutic agents that could be used to treat and, ultimately, prevent it. Contributors discuss the biochemistry and cell biology of amyloid -protein precursor (APP), tau, presenilin, -secretase, and apolipoprotein E and their involvement in Alzheimer disease. They also review the clinical, neuropathological, imaging, and biomarker phenotypes of the disease; genetic alterations associated with the disorder; and epidemiological insights into its causation and pathogenesis. This comprehensive volume, which includes discussions of therapeutic strategies that are currently used or under development, is a vital reference for neurobiologists, cell biologists, pathologists, and other scientists pursuing the biological basis of Alzheimer disease, as well as investigators, clinicians, and students interested in its pathogenesis, treatment, and prevention.
Author: Sujata Dash
Publisher: John Wiley & Sons
ISBN: 111971124X
Category : Computers
Languages : en
Pages : 450
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Book Description
BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.
