Machine Learning And Deep Learning In Neuroimaging Data Analysis
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Machine Learning And Deep Learning In Neuroimaging Data Analysis
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Author : Anitha S. Pillai
language : en
Publisher:
Release Date : 2024
Machine Learning And Deep Learning In Neuroimaging Data Analysis written by Anitha S. Pillai and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with Artificial intelligence 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 both AI experts as well as medical practitioners, chapters cover the majority of neuro problems that use neuroimaging for diagnosis, along with case studies and directions for future research"--
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.
Machine Learning And Deep Learning In Medical Data Analytics And Healthcare Applications
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Author : Om Prakash Jena
language : en
Publisher: CRC Press
Release Date : 2022-02-25
Machine Learning And Deep Learning In Medical Data Analytics And Healthcare Applications written by Om Prakash Jena and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-25 with Computers categories.
Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging, automation, robotic surgery, electronic smart records creation, outbreak prediction, medical image analysis, and radiation treatments. This book aims to endow different communities with the innovative advances in theory, analytical results, case studies, numerical simulation, modeling, and computational structuring in the field of ML/DL models for healthcare applications. It will reveal different dimensions of ML/DL applications and will illustrate their use in the solution of assorted real-world biomedical and healthcare problems. Features: Covers the fundamentals of ML and DL in the context of healthcare applications Discusses various data collection approaches from various sources and how to use them in ML/DL models Integrates several aspects of AI-based computational intelligence such as ML and DL from diversified perspectives which describe recent research trends and advanced topics in the field Explores the current and future impacts of pandemics and risk mitigation in healthcare with advanced analytics Emphasizes feature selection as an important step in any accurate model simulation where ML/DL methods are used to help train the system and extract the positive solution implicitly This book is a valuable source of information for researchers, scientists, healthcare professionals, programmers, and graduate-level students interested in understanding the applications of ML/DL in healthcare scenarios. Dr. Om Prakash Jena is an Assistant Professor in the Department of Computer Science, Ravenshaw University, Cuttack, Odisha, India. Dr. Bharat Bhushan is an Assistant Professor of Department of Computer Science and Engineering (CSE) at the School of Engineering and Technology, Sharda University, Greater Noida, India. Dr. Utku Kose is an Associate Professor in Suleyman Demirel University, Turkey.
Data Analytics And Ai
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Author : Jay Liebowitz
language : en
Publisher: CRC Press
Release Date : 2020-08-06
Data Analytics And Ai written by Jay Liebowitz and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-06 with Computers categories.
Analytics and artificial intelligence (AI), what are they good for? The bandwagon keeps answering, absolutely everything! Analytics and artificial intelligence have captured the attention of everyone from top executives to the person in the street. While these disciplines have a relatively long history, within the last ten or so years they have exploded into corporate business and public consciousness. Organizations have rushed to embrace data-driven decision making. Companies everywhere are turning out products boasting that "artificial intelligence is included." We are indeed living in exciting times. The question we need to ask is, do we really know how to get business value from these exciting tools? Unfortunately, both the analytics and AI communities have not done a great job in collaborating and communicating with each other to build the necessary synergies. This book bridges the gap between these two critical fields. The book begins by explaining the commonalities and differences in the fields of data science, artificial intelligence, and autonomy by giving a historical perspective for each of these fields, followed by exploration of common technologies and current trends in each field. The book also readers introduces to applications of deep learning in industry with an overview of deep learning and its key architectures, as well as a survey and discussion of the main applications of deep learning. The book also presents case studies to illustrate applications of AI and analytics. These include a case study from the healthcare industry and an investigation of a digital transformation enabled by AI and analytics transforming a product-oriented company into one delivering solutions and services. The book concludes with a proposed AI-informed data analytics life cycle to be applied to unstructured data.
Mental Health Prediction Using Machine Learning And Deep Learning Technology
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Author : Bandana Mahapatra
language : en
Publisher: CRC Press
Release Date : 2025-07-04
Mental Health Prediction Using Machine Learning And Deep Learning Technology written by Bandana Mahapatra and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-04 with Business & Economics categories.
Today the integration of technologies like Machine Learning (ML) and Deep Learning (DL) are enabling us to understand, predict, and manage the rising mental health concerns better. This volume provides a comprehensive roadmap for researchers, practitioners, and enthusiasts to explore how artificial intelligence can revolutionize mental healthcare. The book delves into the cutting-edge innovations in predictive modeling, offering insights into how ML and DL algorithms can analyze complex psychological data, detect early warning signs, and predict mental health outcomes. Designed for a diverse audience, including data scientists, mental health professionals, and students, it combines technical rigor with real-world applications. With case studies, hands-on examples, and future-forward discussions, this book empowers readers to contribute to the next wave of mental health solutions powered by AI.
Data Analysis For Neurodegenerative Disorders
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Author : Deepika Koundal
language : en
Publisher: Springer Nature
Release Date : 2023-05-31
Data Analysis For Neurodegenerative Disorders written by Deepika Koundal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-31 with Medical categories.
This book explores the challenges involved in handling medical big data in the diagnosis of neurological disorders. It discusses how to optimally reduce the number of neuropsychological tests during the classification of these disorders by using feature selection methods based on the diagnostic information of enrolled subjects. The book includes key definitions/models and covers their applications in different types of signal/image processing for neurological disorder data. An extensive discussion on the possibility of enhancing the abilities of AI systems using the different data analysis is included. The book recollects several applicable basic preliminaries of the different AI networks and models, while also highlighting basic processes in image processing for various neurological disorders. It also reports on several applications to image processing and explores numerous topics concerning the role of big data analysis in addressing signal and image processing in various real-world scenarios involving neurological disorders. This cutting-edge book highlights the analysis of medical data, together with novel procedures and challenges for handling neurological signals and images. It will help engineers, researchers and software developers to understand the concepts and different models of AI and data analysis. To help readers gain a comprehensive grasp of the subject, it focuses on three key features: ● Presents outstanding concepts and models for using AI in clinical applications involving neurological disorders, with clear descriptions of image representation, feature extraction and selection. ● Highlights a range of techniques for evaluating the performance of proposed CAD systems for the diagnosis of neurological disorders. ● Examines various signal and image processing methods for efficient decision support systems. Soft computing, machine learning and optimization algorithms are also included to improve the CAD systems used.
Advances Of Neuroimaging And Data Analysis
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Author : Jue Zhang
language : en
Publisher: Frontiers Media SA
Release Date : 2020-06-05
Advances Of Neuroimaging And Data Analysis written by Jue Zhang 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 2020-06-05 with categories.
Artificial Intelligence For Medical Image Analysis Of Neuroimaging Data
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Author : Nianyin Zeng
language : en
Publisher: Frontiers Media SA
Release Date : 2020-07-03
Artificial Intelligence For Medical Image Analysis Of Neuroimaging Data written by Nianyin Zeng 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 2020-07-03 with categories.
Advances In Artificial Intelligence And Machine Learning
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Author : N. R. Shetty
language : en
Publisher: Springer Nature
Release Date : 2025-07-25
Advances In Artificial Intelligence And Machine Learning 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 2025-07-25 with Computers categories.
This book features papers from the International Conference on Emerging Research in Computing, Information, Communication, Artificial Intelligence, and Machine Learning (ERCICAM 2024). It serves as an interdisciplinary platform for researchers, professional engineers, scientists, educators, and technologists to discuss, debate, and promote advancements in research and technology within the evolving fields of computing, information, communication, and their applications. Topics covered include the Internet of Things (IoT), wireless communications, image and video processing, parallel and distributed computing, and smart grid applications, among others. The book explores these emerging research areas and acts as a valuable resource for both researchers and practicing engineers.
Machine Learning In Biomedical And Health Informatics
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Author : Sudip Kumar Sahana
language : en
Publisher: CRC Press
Release Date : 2025-09-23
Machine Learning In Biomedical And Health Informatics written by Sudip Kumar Sahana and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-23 with Technology & Engineering categories.
Machine learning is playing an indispensable role in framing clinical decisions and enhancing accuracy. This new book offers a comprehensive take on the field of biomedical and health informatics, discussing topics that include predictive health analytics, pandemic management, AI ethics, application and integration of Internet of Things and machine learning for effective healthcare, and more. The book covers a range of bioinformatics tools and methods and their relation to drug designing and drug screening using ML. Several chapters cover clustering techniques and other methods for analyzing human heart-related disorders. The authors also explore the use of ML in creating adaptive therapies for using chemotherapy and androgen deprivation therapy for prostate cancer and for tracking diseases such as Parkinson’s Speech, Covid-19, and others. Case studies are included that demonstrate the practical use of ML in healthcare informatics.