Use Of Machine Learning Technology In The Diagnosis Of Alzheimer S Disease
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Use Of Machine Learning Technology In The Diagnosis Of Alzheimer S Disease
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Author : Noel O'Kelly
language : en
Publisher:
Release Date : 2016
Use Of Machine Learning Technology In The Diagnosis Of Alzheimer S Disease written by Noel O'Kelly and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Alzheimer's disease (AD) is thought to be the most common cause of dementia and it is estimated that only 1-in-4 people with Alzheimer's are correctly diagnosed in a timely fashion. While no definitive cure is available, when the impairment is still mild the symptoms can be managed and treatment is most effective when it is started before significant downstream damage occurs, i.e., at the stage of mild cognitive impairment (MCI) or even earlier. AD is clinically diagnosed by physical and neurological examination, and through neuropsychological and cognitive tests. There is a need to develop better diagnostic tools, which is what this thesis addresses. Dublin City University School of Nursing and Human Sciences runs a memory clinic, Memory Works where subjects concerned about possible dementia come to seek clarity. Data collected at interview is recorded and one aim of the work in this thesis is to explore the use of machine learning techniques to generate a classifier that can assist in screening new individuals for different stages of AD. However, initial analysis of the features stored in the Memory Works database indicated that there is an insufficient number of instances available (about 120 at this time) to train a machine learning model to accurately predict AD stage on new test cases. The National Azheimers Cordinating Center (NACC) in the U.S collects data from National Institute for Aging (NIA)-funded Alzheimer's Disease Centers (ADCs) and maintains a large database of standardized clinical and neuropathological research data from these ADCs. NACC data are freely available to researchers and we have been given access to 105,000 records from the NACC. We propose to use this dataset to test the hypothesis that a machine learning classifier can be generated to predict the dementia status for new, previously unseen subjects. We will also, by experiment, establish both the minimum number of instances required and the most important features from assessment interviews, to use for this prediction.
The Application Of Artificial Intelligence In Diagnosis And Intervention Of Alzheimer S Disease
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Author : Peng Xu
language : en
Publisher: Frontiers Media SA
Release Date : 2022-11-15
The Application Of Artificial Intelligence In Diagnosis And Intervention Of Alzheimer S Disease written by Peng Xu 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 2022-11-15 with Science categories.
Machine Learning And Deep Learning Techniques For Medical Science
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Author : K. Gayathri Devi
language : en
Publisher: CRC Press
Release Date : 2022-05-11
Machine Learning And Deep Learning Techniques For Medical Science written by K. Gayathri Devi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-11 with Technology & Engineering categories.
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).
Bio Inspired Algorithms And Devices For Treatment Of Cognitive Diseases Using Future Technologies
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Author : Gupta, Shweta
language : en
Publisher: IGI Global
Release Date : 2022-02-11
Bio Inspired Algorithms And Devices For Treatment Of Cognitive Diseases Using Future Technologies written by Gupta, Shweta and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-11 with Technology & Engineering categories.
As there are no proper medical tests available to predict certain diseases such as Alzheimer’s and Parkinson’s at an early stage, there is a need to further study and consider the potential uses of bio- and nature-inspired algorithms and future technologies such as machine learning in correlation to disease detection and treatment. Bio-Inspired Algorithms and Devices for Treatment of Cognitive Diseases Using Future Technologies considers new tools for early detection of cognitive brain diseases using devices and algorithms whose basic concept is taken from nature and discusses design, analysis, and application of various bionics or bio-inspired algorithms. Covering topics such as depression and cognitive science, this publication is an ideal resource for researchers, academicians, industry professionals, psychologists, psychiatrists, nurses, engineers, instructors, and students.
Driving Smart Medical Diagnosis Through Ai Powered Technologies And Applications
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Author : Khang, Alex
language : en
Publisher: IGI Global
Release Date : 2024-02-26
Driving Smart Medical Diagnosis Through Ai Powered Technologies And Applications written by Khang, Alex and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-26 with Medical categories.
Academic scholars face the daunting challenge of keeping pace with the rapid evolution of innovative technologies. The emergence of AI-driven solutions, deep learning frameworks, and medical robotics introduces a complex terrain, demanding in-depth understanding and analysis. As scholars navigate the intricacies of patient hate speech detection, cardiovascular diseases AI-CDSS, and the revolution in medical diagnostics, a pressing need arises for comprehensive insights that bridge the gap between theoretical knowledge and practical applications. Driving Smart Medical Diagnosis Through AI-Powered Technologies and Applications serves as a solution in this era of transformative healthcare and addresses these challenges head-on. It unravels the complexities surrounding the implementation of AI in healthcare, offering in-depth discussions on the latest breakthroughs. From unraveling the mysteries of AI-driven cataract detection to exploring the implications of decentralized mammography classification, the book is a valuable resource that equips scholars with the knowledge to navigate this innovative landscape.
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
Diagnosis Of Neurological Disorders Based On Deep Learning Techniques
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Author : Jyotismita Chaki
language : en
Publisher: CRC Press
Release Date : 2023-05-15
Diagnosis Of Neurological Disorders Based On Deep Learning Techniques written by Jyotismita Chaki and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-15 with Computers categories.
This book is based on deep learning approaches used for the diagnosis of neurological disorders, including basics of deep learning algorithms using diagrams, data tables, and practical examples, for diagnosis of neurodegenerative and neurodevelopmental disorders. It includes application of feed-forward neural networks, deep generative models, convolutional neural networks, graph convolutional networks, and recurrent neural networks in the field of diagnosis of neurological disorders. Along with this, data preprocessing including scaling, correction, trimming, and normalization is also included. Offers a detailed description of the deep learning approaches used for the diagnosis of neurological disorders. Demonstrates concepts of deep learning algorithms using diagrams, data tables, and examples for the diagnosis of neurodegenerative, neurodevelopmental, and psychiatric disorders. Helps build, train, and deploy different types of deep architectures for diagnosis. Explores data preprocessing techniques involved in diagnosis. Includes real-time case studies and examples. This book is aimed at graduate students and researchers in biomedical imaging and machine learning.
Artificial Intelligence For Information Management A Healthcare Perspective
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Author : K. G. Srinivasa
language : en
Publisher: Springer Nature
Release Date : 2021-05-20
Artificial Intelligence For Information Management A Healthcare Perspective written by K. G. Srinivasa and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-20 with Technology & Engineering categories.
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.
Early Alzheimer S Detection With Machine Learning
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Author : Muhammed Niyas
language : en
Publisher: Meem Publishers
Release Date : 2023-07-11
Early Alzheimer S Detection With Machine Learning written by Muhammed Niyas and has been published by Meem Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-11 with categories.
Alzheimer's Disease is a progressive neurodegenerative disorder that affects millions of people worldwide. Detecting this condition in its early stages is critical for timely intervention and better management of the disease. "Early Detection of Alzheimer's Disease using Machine Learning Algorithms" presents a groundbreaking approach to identify early signs of Alzheimer's through advanced machine learning techniques. By harnessing the power of machine learning algorithms, this innovative system analyzes vast amounts of data, including cognitive assessments, brain imaging, and genetic markers. The algorithms can recognize subtle patterns and anomalies indicative of Alzheimer's disease, even before noticeable symptoms manifest. This cutting-edge technology holds great promise in transforming healthcare by enabling early identification of Alzheimer's, potentially leading to more effective treatments and therapies. Moreover, it can provide valuable insights for researchers and medical professionals to better understand the disease's progression and improve patient care. The utilization of machine learning algorithms not only enhances the accuracy and efficiency of Alzheimer's detection but also expedites the diagnostic process, reducing the burden on both patients and healthcare providers. As this field continues to evolve, the application of machine learning in Alzheimer's detection brings hope for a future with improved quality of life for those affected by this challenging condition. Early Alzheimer's Detection with Machine Learning represents a significant leap in the fight against Alzheimer's, offering a beacon of hope for early intervention, better care, and improved outcomes for individuals and their families facing this debilitating disease.
Artificial Intelligence Machine Learning In Nuclear Medicine And Hybrid Imaging
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Author : Patrick Veit-Haibach
language : en
Publisher: Springer Nature
Release Date : 2022-06-22
Artificial Intelligence Machine Learning In Nuclear Medicine And Hybrid Imaging written by Patrick Veit-Haibach and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-22 with Medical categories.
This book includes detailed explanations of the underlying technologies and concepts used in Artificial Intelligence (AI) and Machine Learning (ML) in the context of nuclear medicine and hybrid imaging. A diverse team of authors, including pioneers in the field and respected experts from leading international institutions, share their insights, opinions and outlooks on this exciting topic. A wide range of clinical applications are discussed, from brain applications to body indications, as well as the applicability of AI and ML for cardio-vascular conditions. The book also considers the potential impact of theranostics. To balance the technology-heavy and disease-specific applications, it also discusses ethical / legal issues, economic realities and the human factor, the physician. Though this discussion is not based on research and outcomes, it provides important insights into the ramifications of how AI and ML could transform Nuclear Medicine and Hybrid Imaging practice. As the first work highlighting the role of these concepts specifically in this field, rather than for medical imaging in general, this book offers a valuable resource for Nuclear Medicine Physicians, Radiologists, Physicists, Medical Imaging Administrators and Nuclear Medicine Technologists alike.