Multimodal Data Fusion For Bioinformatics Artificial Intelligence
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Multimodal Data Fusion For Bioinformatics Artificial Intelligence
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Author : Umesh Kumar Lilhore
language : en
Publisher: John Wiley & Sons
Release Date : 2025-01-14
Multimodal Data Fusion For Bioinformatics Artificial Intelligence written by Umesh Kumar Lilhore and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-14 with Computers categories.
Multimodal Data Fusion for Bioinformatics Artificial Intelligence is a must-have for anyone interested in the intersection of AI and bioinformatics, as it delves into innovative data fusion methods and their applications in ‘omics’ research while addressing the ethical implications and future developments shaping the field today. Multimodal Data Fusion for Bioinformatics Artificial Intelligence is an indispensable resource for those exploring how cutting-edge data fusion methods interact with the rapidly developing field of bioinformatics. Beginning with the basics of integrating different data types, this book delves into the use of AI for processing and understanding complex “omics” data, ranging from genomics to metabolomics. The revolutionary potential of AI techniques in bioinformatics is thoroughly explored, including the use of neural networks, graph-based algorithms, single-cell RNA sequencing, and other cutting-edge topics. The second half of the book focuses on the ethical and practical implications of using AI in bioinformatics. The tangible benefits of these technologies in healthcare and research are highlighted in chapters devoted to precision medicine, drug development, and biomedical literature. The book addresses a wide range of ethical concerns, from data privacy to model interpretability, providing readers with a well-rounded education on the subject. Finally, the book explores forward-looking developments such as quantum computing and augmented reality in bioinformatics AI. This comprehensive resource offers a bird’s-eye view of the intersection of AI, data fusion, and bioinformatics, catering to readers of all experience levels.
Multimodal Data Fusion For Bioinformatics Artificial Intelligence
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Author : Umesh Kumar Lilhore
language : en
Publisher: John Wiley & Sons
Release Date : 2025-03-05
Multimodal Data Fusion For Bioinformatics Artificial Intelligence written by Umesh Kumar Lilhore and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-05 with Computers categories.
Multimodal Data Fusion for Bioinformatics Artificial Intelligence is a must-have for anyone interested in the intersection of AI and bioinformatics, as it delves into innovative data fusion methods and their applications in ‘omics’ research while addressing the ethical implications and future developments shaping the field today. Multimodal Data Fusion for Bioinformatics Artificial Intelligence is an indispensable resource for those exploring how cutting-edge data fusion methods interact with the rapidly developing field of bioinformatics. Beginning with the basics of integrating different data types, this book delves into the use of AI for processing and understanding complex “omics” data, ranging from genomics to metabolomics. The revolutionary potential of AI techniques in bioinformatics is thoroughly explored, including the use of neural networks, graph-based algorithms, single-cell RNA sequencing, and other cutting-edge topics. The second half of the book focuses on the ethical and practical implications of using AI in bioinformatics. The tangible benefits of these technologies in healthcare and research are highlighted in chapters devoted to precision medicine, drug development, and biomedical literature. The book addresses a wide range of ethical concerns, from data privacy to model interpretability, providing readers with a well-rounded education on the subject. Finally, the book explores forward-looking developments such as quantum computing and augmented reality in bioinformatics AI. This comprehensive resource offers a bird’s-eye view of the intersection of AI, data fusion, and bioinformatics, catering to readers of all experience levels.
Kernel Based Data Fusion For Machine Learning
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Author : Shi Yu
language : en
Publisher: Springer
Release Date : 2011-03-29
Kernel Based Data Fusion For Machine Learning written by Shi Yu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-29 with Computers categories.
Data fusion problems arise frequently in many different fields. This book provides a specific introduction to data fusion problems using support vector machines. In the first part, this book begins with a brief survey of additive models and Rayleigh quotient objectives in machine learning, and then introduces kernel fusion as the additive expansion of support vector machines in the dual problem. The second part presents several novel kernel fusion algorithms and some real applications in supervised and unsupervised learning. The last part of the book substantiates the value of the proposed theories and algorithms in MerKator, an open software to identify disease relevant genes based on the integration of heterogeneous genomic data sources in multiple species. The topics presented in this book are meant for researchers or students who use support vector machines. Several topics addressed in the book may also be interesting to computational biologists who want to tackle data fusion challenges in real applications. The background required of the reader is a good knowledge of data mining, machine learning and linear algebra.
Integrating Neurocomputing With Artificial Intelligence
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Author : Abhishek Kumar
language : en
Publisher: John Wiley & Sons
Release Date : 2025-06-09
Integrating Neurocomputing With Artificial Intelligence written by Abhishek Kumar and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-09 with Technology & Engineering categories.
Integrating Neurocomputing with Artificial Intelligence provides unparalleled insights into the cutting-edge convergence of neuroscience and computing, enriched with real-world case studies and expert analyses that harness the transformative potential of neurocomputing in various disciplines. Integrating Neurocomputing with Artificial Intelligence is a comprehensive volume that delves into the forefront of the neurocomputing landscape, offering a rich tapestry of insights and cutting-edge innovations. This volume unfolds as a carefully curated collection of research, showcasing multidimensional perspectives on the intersection of neuroscience and computing. Readers can expect a deep exploration of fundamental theories, methodologies, and breakthrough applications that span the spectrum of neurocomputing. Throughout the book, readers will find a wealth of case studies and real-world examples that exemplify how neurocomputing is being harnessed to address complex challenges across different disciplines. Experts and researchers in the field contribute their expertise, presenting in-depth analyses, empirical findings, and forward-looking projections. Integrating Neurocomputing with Artificial Intelligence serves as a gateway to this fascinating domain, offering a comprehensive exploration of neurocomputing’s foundations, contemporary developments, ethical considerations, and future trajectories. It embodies a collective endeavor to drive progress and unlock the potential of neurocomputing, setting the stage for a future where artificial intelligence is not merely artificial, but profoundly inspired by the elegance and efficiency of the human brain.
Networked Sensing Systems
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Author : Rajesh Kumar Dhanaraj
language : en
Publisher: John Wiley & Sons
Release Date : 2025-03-18
Networked Sensing Systems written by Rajesh Kumar Dhanaraj and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-18 with Computers categories.
Networked Sensing Systems is essential for anyone seeking innovative and sustainable solutions across diverse sectors. It explores the integration of cutting-edge IoT technologies and digital transformation aimed at enhancing resource efficiency and addressing climate change challenges. With today’s advancements in wireless and mobile connectivity, Internet of Things (IoT) sensor technologies, and digital innovation, sustainability principles are increasingly reinforcing one another. To transition to more resource-efficient solutions, use resources responsibly, and streamline operations, businesses must embrace digital transformation. Potential application areas include energy management, air pollution monitoring, fleet management, water management, and agriculture. Simultaneously, the expansion of IoT deployments and their integration into the contexts of 5G and emerging 6G mobile networking necessitate that the solutions themselves be green and sustainable. This includes incorporating energy- and environmentally-conscious technical solutions for communications. By offering previously unattainable solutions, networked sensing can contribute to a more sustainable society by enabling the collection of data from heterogeneous sources in unique and novel ways. Additionally, the networking-based solutions themselves must be sustainable and environmentally friendly. For example, optimizing network architecture and relocating network equipment to strategic locations can significantly reduce energy waste. These goals drive the search for improved sensing technologies, emphasizing energy-efficient mobile sensing devices. The goal of Networked Sensing Systems is to present and highlight the latest developments in sustainable networked sensing systems across a variety of contexts, all united by the aim of enhancing human well-being and combating climate change. Regardless of the area of expertise, this work seeks to offer practical solutions to the major challenges of building a sustainable smart society 5.0. This book serves as a platform to discuss networked sensing systems for a sustainable society, focusing on systems and applications based on mobile computing and wireless networks, while adopting multidisciplinary approaches that emphasize the human element in addressing these challenges.
Artificial Intelligence And Bioinformatics In Cancer An Interdisciplinary Approach
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Author : Nima Rezaei
language : en
Publisher: Springer Nature
Release Date : 2025-05-30
Artificial Intelligence And Bioinformatics In Cancer An Interdisciplinary Approach written by Nima Rezaei and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-30 with Medical categories.
The “Artificial Intelligence and Bioinformatics in Cancer: An Interdisciplinary Approach” is the eighteenth volume of the “Interdisciplinary Cancer Research” series, publishes comprehensive volume on the advances of machine learning and bioinformatics in cancer. The volume starts with a chapter on application of artificial intelligence for early diagnosis of cancer. Then digital health technologies in cancer care and research is discussed. Unveiling cancer complexity: machine learning insights into multi-omics data and the role of integrated bioinformatics in cancer research are also discussed. In silico and biophysical approaches in cancer research and in silico methods and targeted receptors used in cancer studies are explained in the following chapters. The modeling uncertain growth and diffusion in cancer tumors with heterogeneous cell mutations, imaging tumor metabolism and its heterogeneity with special focus on radiomics and artificial intelligence are also discussed. Mathematical modeling of cancer tumor dynamics as well as recent advances in artificial intelligence for cancer treatment are presented, while signature-based drug repositioning for drug discovery employing machine learning tools is also discussed. After a chapter on mathematical analysis of cancer-tumor models, the subsequent chapters discuss on the role of artificial intelligence in colorectal cancer, breast cancer, lung cancer, brain tumor, and cervical cancer. This is the main concept of Cancer Immunology Project (CIP), which is a part of Universal Scientific Education and Research Network (USERN). This interdisciplinary book will be of special value for oncologists who wish to have an update on application of artificial intelligence in diagnosis and treatment of cancers.
Enablers Barriers And Challenges For Inclusive Curriculum
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Author : Charamba, Erasmos
language : en
Publisher: IGI Global
Release Date : 2025-05-29
Enablers Barriers And Challenges For Inclusive Curriculum written by Charamba, Erasmos and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-29 with Education categories.
United Nations’ 2030 Agenda for Sustainable Development Goal 4 seeks to ensure inclusive and equitable quality education and to promote lifelong learning opportunities for all learners. Education can only unfold its full potential to transform our world if it is approached from a lifelong learning perspective. In this way, learners’ lives are brought closer to education through integrated, multi-sectoral approaches that draw the focus from supply to demand. In order to achieve this, institutions and educators need to come up with strategies that are inclusive regardless of the student's intellectual challenges, physical stature, gender, language, culture, or mode of learning. Enablers, Barriers, and Challenges for Inclusive Curriculum examines the impact of enablers and barriers on education for students and teachers. It discusses promoting inclusive curriculum in face-to-face, online, and blended learning environments. Covering topics such as educational transitions, large classrooms, and school-going young mothers, this book is an excellent resource for educators, student teachers, parents, policymakers, professionals, researcher, scholars, academicians, and more.
Bioinformatics And Medical Applications
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Author : A. Suresh
language : en
Publisher: John Wiley & Sons
Release Date : 2022-03-24
Bioinformatics And Medical Applications written by A. Suresh and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-24 with Computers categories.
BIOINFORMATICS AND MEDICAL APPLICATIONS The main topics addressed in this book are big data analytics problems in bioinformatics research such as microarray data analysis, sequence analysis, genomics-based analytics, disease network analysis, techniques for big data analytics, and health information technology. Bioinformatics and Medical Applications: Big Data Using Deep Learning Algorithms analyses massive biological datasets using computational approaches and the latest cutting-edge technologies to capture and interpret biological data. The book delivers various bioinformatics computational methods used to identify diseases at an early stage by assembling cutting-edge resources into a single collection designed to enlighten the reader on topics focusing on computer science, mathematics, and biology. In modern biology and medicine, bioinformatics is critical for data management. This book explains the bioinformatician’s important tools and examines how they are used to evaluate biological data and advance disease knowledge. The editors have curated a distinguished group of perceptive and concise chapters that presents the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to healthcare. Applying deep learning techniques for data-driven solutions in health information allows automated analysis whose method can be more advantageous in supporting the problems arising from medical and health-related information. Audience The primary audience for the book includes specialists, researchers, postgraduates, designers, experts, and engineers, who are occupied with biometric research and security-related issues.
Medical Image Processing
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Author : Satya Prakash Yadav
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2024-09-23
Medical Image Processing written by Satya Prakash Yadav and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-23 with Science categories.
The goal of this book is to facilitate and stimulate cross-disciplinary research in the emerging paradigm of Medical Imaging. Especially this book is to focus on analysing and articulating proven and potential security measures to tightly secure Medical Image applications and services, which are being hosted and delivered through cloud infrastructures and platforms. This book will illustrate the prominent advancements in image processing and how intelligent image-processing techniques can be developed and deployed in the industrial market and for academicians. The readers will get to know all the right and relevant details to be empowered to successfully contribute to their personal and professional growth. The main focus of this book is to bring all the related technologies, novel findings, and managerial applications of Medical Imaging on a single platform to provide great readability, easy understanding, and smooth adaptability of various basic and advanced concepts to Researchers in Medical Engineers, Machine Learning and Data Analysis.
Association Analysis Techniques And Applications In Bioinformatics
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Author : Qingfeng Chen
language : en
Publisher: Springer Nature
Release Date : 2024-04-25
Association Analysis Techniques And Applications In Bioinformatics written by Qingfeng Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-25 with Computers categories.
Advances in experimental technologies have given rise to tremendous amounts of biology data. This not only offers valuable sources of data to help understand biological evolution and functional mechanisms, but also poses challenges for accurate and effective data analysis. This book offers an essential introduction to the theoretical and practical aspects of association analysis, including data pre-processing, data mining methods/algorithms, and tools that are widely applied for computational biology. It covers significant recent advances in the field, both foundational and application-oriented, helping readers understand the basic principles and emerging techniques used to discover interesting association patterns in diverse and heterogeneous biology data, such as structure-function correlations, and complex networks with gene/protein regulation. The main results and approaches are described in an easy-to-follow way and accompanied by sufficientreferences and suggestions for future research. This carefully edited monograph is intended to provide investigators in the fields of data mining, machine learning, artificial intelligence, and bioinformatics with a profound guide to the role of association analysis in computational biology. It is also very useful as a general source of information on association analysis, and as an overall accompanying course book and self-study material for graduate students and researchers in both computer science and bioinformatics.