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Author: Osval Antonio Montesinos López Publisher: Springer Nature ISBN: 3030890104 Category : Technology & Engineering Languages : en Pages : 707
Book Description
This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.
Author: Osval Antonio Montesinos López Publisher: Springer Nature ISBN: 3030890104 Category : Technology & Engineering Languages : en Pages : 707
Book Description
This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.
Author: Vikas Khullar Publisher: CRC Press ISBN: 1003825591 Category : Computers Languages : en Pages : 294
Book Description
The artificial intelligence-based framework, algorithms, and applications presented in this book take the perspective of Society 5.0 – a social order supported by innovation in data, information, and knowledge. It showcases current case studies of Society 5.0 in diverse areas such as healthcare, smart cities, and infrastructure. Key Features: Elaborates on the use of big data, cyber-physical systems, robotics, augmented-virtual reality, and cybersecurity as pillars for Society 5.0. Showcases the use of artificial intelligence, architecture, frameworks, and distributed and federated learning structures in Society 5.0. Discusses speech recognition, image classification, robotic process automation, natural language generation, and decision support automation. Elucidates the application of machine learning, deep learning, fuzzy-based systems, and natural language processing. Includes case studies on the application of Society 5.0 aspects in educational, medical, infrastructure, and smart cities. The book is intendended especially for graduate and postgraduate students, and academic researchers in the fields of computer science and engineering, electrical engineering, and information technology.
Author: Galety, Mohammad Gouse Publisher: IGI Global ISBN: Category : Technology & Engineering Languages : en Pages : 359
Book Description
In geospatial analysis, navigating the complexities of data interpretation and analysis presents a formidable challenge. Traditional methods often need to efficiently handle vast volumes of geospatial data while providing insightful and actionable results. Scholars and practitioners grapple with manual or rule-based approaches, hindering progress in understanding and addressing pressing issues such as climate change, urbanization, and resource management. Ethics, Machine Learning, and Python in Geospatial Analysis offers a solution to the challenges faced by leveraging the extensive library support and user-friendly interface of Python and machine learning. The book’s meticulously crafted chapters guide readers through the intricacies of Python programming and its application in geospatial analysis, from fundamental concepts to advanced techniques.
Author: Publisher: Elsevier ISBN: 0443295255 Category : Technology & Engineering Languages : en Pages : 320
Book Description
Advances in Agronomy, Volume 184, the latest release in this leading reference on agronomy, contains a variety of updates and highlights new advances in the field. Each chapter is written by an international board of authors, with this new release including new chapters on The Role of Artificial Intelligence in Crop Improvement, Dealing with the Impact of Climate Change-Induced Drought on the Management of Soil, Challenges and Emerging Opportunities of Weed Management in Organic Agriculture, The Broadbalk Wheat Experiment, Rothamsted, UK: Crop Yields and Soil Changes During the Last 50 Years. Includes numerous, timely, state-of-the-art reviews on the latest advancements in agronomy Features distinguished, well recognized authors from around the world Builds upon this venerable and iconic review series Covers the extensive variety and breadth of subject matter in the crop and soil sciences
Author: Srivastava, Pramod Kumar Publisher: IGI Global ISBN: Category : Computers Languages : en Pages : 315
Book Description
Technology is constantly evolving, and machine learning is positioned to become a pivotal tool with the power to transform industries and revolutionize everyday life. This book underscores the urgency of leveraging the latest machine learning methodologies and theoretical advancements, all while harnessing a wealth of realistic data and affordable computational resources. Machine learning is no longer confined to theoretical domains; it is now a vital component in healthcare, manufacturing, education, finance, law enforcement, and marketing, ushering in an era of data-driven decision-making. Academic scholars seeking to unlock the potential of machine learning in the context of Industry 5.0 and advanced IoT applications will find that the groundbreaking book, Methodologies, Frameworks, and Applications of Machine Learning, introduces an unmissable opportunity to delve into the forefront of modern research and application. This book offers a wealth of knowledge and practical insights across a wide array of topics, ranging from conceptual frameworks and methodological approaches to the application of probability theory, statistical techniques, and machine learning in domains as diverse as e-government, healthcare, cyber-physical systems, and sustainable development, this comprehensive guide equips you with the tools to navigate the complexities of Industry 5.0 and the Internet of Things (IoT).
Author: Walid A. Zgallai Publisher: Elsevier ISBN: 0323954634 Category : Science Languages : en Pages : 437
Book Description
Artificial Intelligence and Image Processing in Medical Imaging deals with the applications of processing medical images with a view of improving the quality of the data in order to facilitate better decision- making. The book covers the basics of medical imaging and the fundamentals of image processing. It explains spatial and frequency domain applications of image processing, introduces image compression techniques and their applications, and covers image segmentation techniques and their applications. The book includes object detection and classification applications and provides an overall background to statistical analysis in biomedical systems. The role of Machine Learning, including Neural Networks, Deep Learning, and the implications of the expansion of artificial intelligence is also covered. With contributions from prominent researchers worldwide, this book provides up-to-date and comprehensive coverage of AI applications in image processing where readers will find the latest information with clear examples and illustrations. Provides the latest comprehensive coverage of the developments of AI techniques and the principles of medical imaging Covers all aspects of medical imaging, from acquisition, the use of hardware and software, image analysis and implementation of AI in problem solving Provides examples of medical imaging and how they’re processed, including segmentation, classification, and detection
Author: Mahendra Rai Publisher: Elsevier ISBN: 0323983480 Category : Science Languages : en Pages : 470
Book Description
Nanotechnology Principles in Drug Targeting and Diagnosis focuses on the nanotechnology principles and mechanisms involved in drug targeting, nano carriers and target interactions associated with particular diseases. The book addresses how phytotherapeutics are effective against solid tumors and how they can be used in designing targeted delivery systems. Also addressed is the use of macrophages as the biomimetic carrier for targeting drugs to different organs. Sections cover the nanotechnology-based concepts in drug targeting, strategies for drug targeting, ways to identify drug carrier-target interaction, the concept of an artificial neural network in identifying drug-target interaction, and more. The book's final section concentrates on the role of nanotechnology in medical diagnosis, throwing light on nanoscale sensors for the diagnosis of viruses in the bloodstream and biomarkers indicating various cancers. This is an important reference source for materials scientists and pharmaceutical scientists who want to understand how nanotechnology plays an important role in creating more efficient drug targeting and delivery systems. Provides extensive coverage of methods of drug-carrier-target identification and the capability of artificial intelligence to recognize patterns in patients using these patterns for nanocarrier design Helps readers understand how nanocarriers must be functionalized for effective targeted delivery and how they can be useful tools for personalized and precise treatment of diseases Assesses the role of nanoscale sensors in the early detection of cancer cells in the bloodstream
Author: Momiao Xiong Publisher: CRC Press ISBN: 1498725805 Category : Mathematics Languages : en Pages : 668
Book Description
Big Data in Omics and Imaging: Association Analysis addresses the recent development of association analysis and machine learning for both population and family genomic data in sequencing era. It is unique in that it presents both hypothesis testing and a data mining approach to holistically dissecting the genetic structure of complex traits and to designing efficient strategies for precision medicine. The general frameworks for association analysis and machine learning, developed in the text, can be applied to genomic, epigenomic and imaging data. FEATURES Bridges the gap between the traditional statistical methods and computational tools for small genetic and epigenetic data analysis and the modern advanced statistical methods for big data Provides tools for high dimensional data reduction Discusses searching algorithms for model and variable selection including randomization algorithms, Proximal methods and matrix subset selection Provides real-world examples and case studies Will have an accompanying website with R code The book is designed for graduate students and researchers in genomics, bioinformatics, and data science. It represents the paradigm shift of genetic studies of complex diseases– from shallow to deep genomic analysis, from low-dimensional to high dimensional, multivariate to functional data analysis with next-generation sequencing (NGS) data, and from homogeneous populations to heterogeneous population and pedigree data analysis. Topics covered are: advanced matrix theory, convex optimization algorithms, generalized low rank models, functional data analysis techniques, deep learning principle and machine learning methods for modern association, interaction, pathway and network analysis of rare and common variants, biomarker identification, disease risk and drug response prediction.
Author: Osval Antonio Montesinos López
Author: Osval Antonio Montesinos López
Author: Chao Xu
Author: Vikas Khullar
Author: Galety, Mohammad Gouse
Author: Vijay Rani Rajpal
Author: 
Author: Srivastava, Pramod Kumar
Author: Walid A. Zgallai
Author: Mahendra Rai
Author: Momiao Xiong