Handbook of Machine Learning Applications for Genomics

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Publisher : Springer Nature
ISBN 13 : 9811691584
Total Pages : 222 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Handbook of Machine Learning Applications for Genomics by : Sanjiban Sekhar Roy

Download or read book Handbook of Machine Learning Applications for Genomics written by Sanjiban Sekhar Roy and published by Springer Nature. This book was released on 2022-06-23 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Currently, machine learning is playing a pivotal role in the progress of genomics. The applications of machine learning are helping all to understand the emerging trends and the future scope of genomics. This book provides comprehensive coverage of machine learning applications such as DNN, CNN, and RNN, for predicting the sequence of DNA and RNA binding proteins, expression of the gene, and splicing control. In addition, the book addresses the effect of multiomics data analysis of cancers using tensor decomposition, machine learning techniques for protein engineering, CNN applications on genomics, challenges of long noncoding RNAs in human disease diagnosis, and how machine learning can be used as a tool to shape the future of medicine. More importantly, it gives a comparative analysis and validates the outcomes of machine learning methods on genomic data to the functional laboratory tests or by formal clinical assessment. The topics of this book will cater interest to academicians, practitioners working in the field of functional genomics, and machine learning. Also, this book shall guide comprehensively the graduate, postgraduates, and Ph.D. scholars working in these fields.

Computational Genomics with R

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Publisher : CRC Press
ISBN 13 : 1498781861
Total Pages : 463 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Computational Genomics with R by : Altuna Akalin

Download or read book Computational Genomics with R written by Altuna Akalin and published by CRC Press. This book was released on 2020-12-16 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.

Deep Learning Applications in Image Analysis

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Publisher : Springer Nature
ISBN 13 : 9819937841
Total Pages : 218 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Deep Learning Applications in Image Analysis by : Sanjiban Sekhar Roy

Download or read book Deep Learning Applications in Image Analysis written by Sanjiban Sekhar Roy and published by Springer Nature. This book was released on 2023-07-08 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides state-of-the-art coverage of deep learning applications in image analysis. The book demonstrates various deep learning algorithms that can offer practical solutions for various image-related problems; also how these algorithms are used by scientists and scholars in industry and academia. This includes autoencoder and deep convolutional generative adversarial network in improving classification performance of Bangla handwritten characters, dealing with deep learning-based approaches using feature selection methods for automatic diagnosis of covid-19 disease from x-ray images, imbalance image data sets of classification, image captioning using deep transfer learning, developing a vehicle over speed detection system, creating an intelligent system for video-based proximity analysis, building a melanoma cancer detection system using deep learning, plant diseases classification using AlexNet, dealing with hyperspectral images using deep learning, chest x-ray image classification of pneumonia disease using efficient net and inceptionv3. The book also addresses the difficulty of implementing deep learning in terms of computation time and the complexity of reasoning and modelling different types of data where information is currently encoded. Each chapter has the application of various new or existing deep learning models such as Deep Neural Network (DNN) and Deep Convolutional Neural Networks (DCNN). The detailed utilization of deep learning packages that are available in MATLAB, Python and R programming environments have also been discussed, therefore, the readers will get to know about the practical implementation of deep learning as well. The content of this book is presented in a simple and lucid style for professionals, nonprofessionals, scientists, and students interested in the research area of deep learning applications in image analysis.

Machine Learning and IoT Applications for Health Informatics

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Publisher : CRC Press
ISBN 13 : 1040228127
Total Pages : 251 pages
Book Rating : 4.0/5 (42 download)

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Book Synopsis Machine Learning and IoT Applications for Health Informatics by : Pijush Samui

Download or read book Machine Learning and IoT Applications for Health Informatics written by Pijush Samui and published by CRC Press. This book was released on 2024-10-31 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together leading experts from around the world to explore the transformative potential of Machine Learning (ML) and the Internet of Things (IoT) in healthcare. It provides a platform for studying a future where healthcare becomes more precise, personalized, and accessible for all. The book covers recent advancements that will shape the future of healthcare and how artificial intelligence is revolutionizing disease detection, from analyzing chest X-rays for pneumonia to solving the secrets of our genes. It investigates the transformative potential of smart devices, real-time analysis of heart data, and personalized treatment plan creation. It shows how ML and IoT work and presents real-world examples of how they are leading to earlier and more accurate diagnoses and personalized treatments. Therefore, this edited book will be an invaluable resource for researchers, healthcare professionals, data scientists, or simply someone passionate about the future of healthcare. Readers will discover the exciting possibilities that lie ahead at the crossroads of ML, IoT, and health informatics.

Modeling and Applications in Operations Research

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Publisher : CRC Press
ISBN 13 : 1003802796
Total Pages : 285 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Modeling and Applications in Operations Research by : Jyotiranjan Nayak

Download or read book Modeling and Applications in Operations Research written by Jyotiranjan Nayak and published by CRC Press. This book was released on 2023-11-29 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text envisages novel optimization methods that significantly impact real-life problems, starting from inventory control to economic decision-making. It discusses topics such as inventory control, queueing models, timetable scheduling, fuzzy optimization, and the Knapsack problem. The book’s content encompass the following key aspects: Presents a new model based on an unreliable server, wherein the convergence analysis is done using nature-inspired algorithms. Discusses the optimization techniques used in transportation problems, timetable problems, and optimal/dynamic pricing in inventory control. Highlights single and multi-objective optimization problems using pentagonal fuzzy numbers. Illustrates profit maximization inventory model for non-instantaneous deteriorating items with imprecise costs. Showcases nature-inspired algorithms such as particle swarm optimization, genetic algorithm, bat algorithm, and cuckoo search algorithm. The text covers multi-disciplinary real-time problems such as fuzzy optimization of transportation problems, inventory control with dynamic pricing, timetable problem with ant colony optimization, knapsack problem, queueing modeling using the nature-inspired algorithm, and multi-objective fuzzy linear programming. It showcases a comparative analysis for studying various combinations of system design parameters and default cost elements. It will serve as an ideal reference text for graduate students and academic researchers in the fields of industrial engineering, manufacturing engineering, production engineering, mechanical engineering, and mathematics.

Hybrid Computational Intelligent Systems

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Publisher : CRC Press
ISBN 13 : 1000862054
Total Pages : 560 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis Hybrid Computational Intelligent Systems by : Siddhartha Bhattacharyya

Download or read book Hybrid Computational Intelligent Systems written by Siddhartha Bhattacharyya and published by CRC Press. This book was released on 2023-05-03 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hybrid Computational Intelligent Systems – Modeling, Simulation and Optimization unearths the latest advances in evolving hybrid intelligent modeling and simulation of human-centric data-intensive applications optimized for real-time use, thereby enabling researchers to come up with novel breakthroughs in this ever-growing field. Salient features include the fundamentals of modeling and simulation with recourse to knowledge-based simulation, interaction paradigms, and human factors, along with the enhancement of the existing state of art in a high-performance computing setup. In addition, this book presents optimization strategies to evolve robust and failsafe intelligent system modeling and simulation. The volume also highlights novel applications for different engineering problems including signal and data processing, speech, image, sensor data processing, innovative intelligent systems, and swarm intelligent manufacturing systems. Features: A self-contained approach to integrating the principles of hybrid computational ntelligence with system modeling and simulation Well-versed foundation of computational intelligence and its application to real life engineering problems Elucidates essential background, concepts, definitions, and theories thereby putting forward a complete treatment on the subject Effective modeling of hybrid intelligent systems forms the backbone of almost every operative system in real-life Proper simulation of real-time hybrid intelligent systems is a prerequisite for deriving any real-life system solution Optimized system modeling and simulation enable real-time and failsafe operations of the existing hybrid intelligent system solutions Information presented in an accessible way for researchers, engineers, developers, and practitioners from academia and industry working in all major areas and interdisciplinary areas of hybrid computational intelligence and communication systems to evolve human-centered modeling and simulations of real-time data-intensive intelligent systems.

Internet of Things-Based Machine Learning in Healthcare

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Publisher : CRC Press
ISBN 13 : 1040031854
Total Pages : 242 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Internet of Things-Based Machine Learning in Healthcare by : Prasenjit Dey

Download or read book Internet of Things-Based Machine Learning in Healthcare written by Prasenjit Dey and published by CRC Press. This book was released on 2024-06-10 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Internet of Medical Things (IoMT) is a system that collects data from patients with the help of different sensory inputs, e.g., an accelerometer, electrocardiography, and electroencephalography. This text presents both theoretical and practical concepts related to the application of machine learning and Internet of Things (IoT) algorithms in analyzing data generated through healthcare systems. Illustrates the latest technologies in the healthcare domain and the Internet of Things infrastructure for storing smart electronic health records Focuses on the importance of machine learning algorithms and the significance of Internet of Things infrastructure for healthcare systems Showcases the application of fog computing architecture and edge computing in novel aspects of modern healthcare services Discusses unsupervised genetic algorithm-based automatic heart disease prediction Covers Internet of Things–based hardware mechanisms and machine learning algorithms to predict the stress level of patients The text is primarily written for graduate students and academic researchers in the fields of computer science and engineering, biomedical engineering, electrical engineering, and information technology.

Advances in Distributed Computing and Machine Learning

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Publisher : Springer Nature
ISBN 13 : 9819912032
Total Pages : 600 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Advances in Distributed Computing and Machine Learning by : Suchismita Chinara

Download or read book Advances in Distributed Computing and Machine Learning written by Suchismita Chinara and published by Springer Nature. This book was released on 2023-06-27 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of peer-reviewed best selected research papers presented at the Fourth International Conference on Advances in Distributed Computing and Machine Learning (ICADCML 2023), organized by Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Odisha, India, during 15–16 January 2023. This book presents recent innovations in the field of scalable distributed systems in addition to cutting edge research in the field of Internet of Things (IoT) and blockchain in distributed environments.

Smart Computing Techniques in Industrial IoT

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Publisher : Springer Nature
ISBN 13 : 9819774942
Total Pages : 225 pages
Book Rating : 4.8/5 (197 download)

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Book Synopsis Smart Computing Techniques in Industrial IoT by : Chiranji Lal Chowdhary

Download or read book Smart Computing Techniques in Industrial IoT written by Chiranji Lal Chowdhary and published by Springer Nature. This book was released on with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Smart Sensors for Industry 4.0

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Publisher : John Wiley & Sons
ISBN 13 : 1394213565
Total Pages : 260 pages
Book Rating : 4.3/5 (942 download)

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Book Synopsis Smart Sensors for Industry 4.0 by : Brojo Kishore Mishra

Download or read book Smart Sensors for Industry 4.0 written by Brojo Kishore Mishra and published by John Wiley & Sons. This book was released on 2024-09-04 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the essential guide to harnessing the power of cutting-edge smart sensors in Industry 4.0, offering deep insights into fundamentals, fabrication techniques, and real-world IIoT applications, equipping you with the knowledge to revolutionize your industrial processes and stay ahead in the digital era. Over the last decade, technologies like the Internet of Things (IoT), big data, cloud computing, blockchain, artificial intelligence (AI), machine learning, device automation, smart sensors, etc., have become highly developed fundamental supports of Industry 4.0, replacing the conventional production systems with advanced methods, and thereby endorsing the smart industry vision. Industry 4.0 is more flexible and agile in dealing with several risk factors, further enabling improved productivity and efficiency, distribution, increased profitability, data integrity, and enhancing customer experience in the current commercial environment. For understanding and analyzing the environment, sensors play a major role in performing the measurements based on computation-produced results from the surrounding environment. Sensors have a wide range of applications for smart industrial operations. The evolution of flexible, low-cost, and multipurpose sensors and their system integration has been examined to develop advanced devices with applications in numerous fields of technology. With the development of both the Internet of Things (IoT) and the Industrial IoT (IIoT), advanced sensors and their associated applications are developing, resulting in the necessity for IoT sensors to be used for several industrial applications. Beneficial aspects of this book include: The latest research in materials and methodology for the fabrication of intelligent sensors, its IoT system integration, and IIoT applications are brought together; Promotes a vision towards making sensor-based monitoring and control of smart industry; Recent advances and challenges of smart sensors are discussed with an emphasis on unmet challenges and future directions of a roadmap to Industry 4.0. Audience This book is highly recommended to a wide range of researchers and industry engineers working in the area of fabrication and integration of industrial smart sensors for IIoT applications, advanced materials for sensor technology, fabrication and characterization of IoT sensors, development of low-cost sensors, sensor system design and integration, and its industrial applications. Post-graduate students from different streams like computer science, electronics and electrical engineering, information technology, electronic communication, etc. will benefit from reading this book.

Handbook of Biomarkers and Precision Medicine

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Publisher : CRC Press
ISBN 13 : 0429574622
Total Pages : 953 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Handbook of Biomarkers and Precision Medicine by : Claudio Carini

Download or read book Handbook of Biomarkers and Precision Medicine written by Claudio Carini and published by CRC Press. This book was released on 2019-04-16 with total page 953 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The field of Biomarkers and Precision Medicine in drug development is rapidly evolving and this book presents a snapshot of exciting new approaches. By presenting a wide range of biomarker applications, discussed by knowledgeable and experienced scientists, readers will develop an appreciation of the scope and breadth of biomarker knowledge and find examples that will help them in their own work." -Maria Freire, Foundation for the National Institutes of Health Handbook of Biomarkers and Precision Medicine provides comprehensive insights into biomarker discovery and development which has driven the new era of Precision Medicine. A wide variety of renowned experts from government, academia, teaching hospitals, biotechnology and pharmaceutical companies share best practices, examples and exciting new developments. The handbook aims to provide in-depth knowledge to research scientists, students and decision makers engaged in Biomarker and Precision Medicine-centric drug development. Features: Detailed insights into biomarker discovery, validation and diagnostic development with implementation strategies Lessons-learned from successful Precision Medicine case studies A variety of exciting and emerging biomarker technologies The next frontiers and future challenges of biomarkers in Precision Medicine Claudio Carini, Mark Fidock and Alain van Gool are internationally recognized as scientific leaders in Biomarkers and Precision Medicine. They have worked for decades in academia and pharmaceutical industry in EU, USA and Asia. Currently, Dr. Carini is Honorary Faculty at Kings’s College School of Medicine, London, UK. Dr. Fidock is Vice President of Precision Medicine Laboratories at AstraZeneca, Cambridge, UK. Prof.dr. van Gool is Head Translational Metabolic Laboratory at Radboud university medical school, Nijmegen, NL.

Handbook of Molecular Biotechnology

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Publisher : CRC Press
ISBN 13 : 1040005640
Total Pages : 763 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Handbook of Molecular Biotechnology by : Dongyou Liu

Download or read book Handbook of Molecular Biotechnology written by Dongyou Liu and published by CRC Press. This book was released on 2024-09-05 with total page 763 pages. Available in PDF, EPUB and Kindle. Book excerpt: With a history that likely dates back to the dawn of human civilization more than 10,000 years ago, and a record that includes the domestication and selective breeding of plants and animals, the harnessing of fermentation process for bread, cheese, and brewage production, and the development of vaccines against infectious diseases, biotechnology has acquired a molecular focus during the 20th century, particularly following the resolution of DNA double helix in 1953, and the publication of DNA cloning protocol in 1973, and transformed our concepts and practices in disease diagnosis, treatment and prevention, pharmaceutical and industrial manufacturing, animal and plant industry, and food processing. While molecular biotechnology offers unlimited opportunities for improving human health and well-being, animal welfare, agricultural innovation and environmental conservation, a dearth of high quality books that have the clarity of laboratory manuals without distractive procedural details and the thoroughness of well-conversed textbooks appears to dampen the enthusiasm of aspiring students. In attempt to fill this glaring gap, Handbook of Molecular Biotechnology includes four sections, with the first three presenting in-depth coverage on DNA, RNA and protein technologies, and the fourth highlighting their utility in biotechnology. Recognizing the importance of logical reasoning and experimental verification over direct observation and simple description in biotechnological research and development, the Introduction provides pertinent discussions on key strategies (i.e., be first, be better, and be different), effective thinking (lateral, parallel, causal, reverse, and random), and experimental execution, which have proven invaluable in helping advance research projects, evaluate and prepare research reports, and enhance other scientific endeavors. Key features Presents state-of-the-art reviews on DNA, RNA and protein technologies and their biotechnological applications Discusses key strategies, effective thinking, and experimental execution for scientific research and development Fills the gap left by detailed-ridden laboratory manuals and insight-lacking standard textbooks Includes expert contributions from international scientists at the forefront of molecular biotechnology research and development Written by international scientists at the forefront of molecular biotechnology research and development, chapters in this volume cover the histories, principles, and applications of individual techniques/technologies, and constitute stand-alone, yet interlinked lectures that strive to educate as well as to entertain. Besides providing an informative textbook for tertiary students in molecular biotechnology and related fields, this volume serves as an indispensable roadmap for novice scientists in their efforts to acquire innovative skills and establish solid track records in molecular biotechnology, and offers a contemporary reference for scholars, educators, and policymakers wishing to keep in touch with recent developments in molecular biotechnology.

Computational Intelligence for Oncology and Neurological Disorders

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Publisher : CRC Press
ISBN 13 : 1040085628
Total Pages : 292 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Computational Intelligence for Oncology and Neurological Disorders by : Mrutyunjaya Panda

Download or read book Computational Intelligence for Oncology and Neurological Disorders written by Mrutyunjaya Panda and published by CRC Press. This book was released on 2024-07-15 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the advent of computational intelligence-based approaches, such as bio-inspired techniques, and the availability of clinical data from various complex experiments, medical consultants, researchers, neurologists, and oncologists, there is huge scope for CI-based applications in medical oncology and neurological disorders. This book focuses on interdisciplinary research in this field, bringing together medical practitioners dealing with neurological disorders and medical oncology along with CI investigators. The book collects high-quality original contributions, containing the latest developments or applications of practical use and value, presenting interdisciplinary research and review articles in the field of intelligent systems for computational oncology and neurological disorders. Drawing from work across computer science, physics, mathematics, medical science, psychology, cognitive science, oncology, and neurobiology among others, it combines theoretical, applied, computational, experimental, and clinical research. It will be of great interest to any neurology or oncology researchers focused on computational approaches.

Handbook of Research on Mathematical Modeling for Smart Healthcare Systems

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Author :
Publisher : IGI Global
ISBN 13 : 1668445824
Total Pages : 503 pages
Book Rating : 4.6/5 (684 download)

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Book Synopsis Handbook of Research on Mathematical Modeling for Smart Healthcare Systems by : Samanta, Debabrata

Download or read book Handbook of Research on Mathematical Modeling for Smart Healthcare Systems written by Samanta, Debabrata and published by IGI Global. This book was released on 2022-06-24 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in healthcare technologies have offered real-time guidance and technical assistance for diagnosis, monitoring, operation, and interventions. The development of artificial intelligence, machine learning, internet of things technology, and smart computing techniques are crucial in today’s healthcare environment as they provide frictionless and transparent financial transactions and improve the overall healthcare experience. This, in turn, has far-reaching effects on economic, psychological, educational, and organizational improvements in the way we work, teach, learn, and provide care. These advances must be studied further in order to ensure they are adapted and utilized appropriately. The Handbook of Research on Mathematical Modeling for Smart Healthcare Systems presents the latest research findings, ideas, innovations, developments, and applications in the field of modeling for healthcare systems. Furthermore, it presents the application of innovative techniques to complex problems in the case of healthcare. Covering a range of topics such as artificial intelligence, deep learning, and personalized healthcare services, this reference work is crucial for engineers, healthcare professionals, researchers, academicians, scholars, practitioners, instructors, and students.

Innovations in Intelligent Computing and Communication

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Publisher : Springer Nature
ISBN 13 : 303123233X
Total Pages : 438 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Innovations in Intelligent Computing and Communication by : Mrutyunjaya Panda

Download or read book Innovations in Intelligent Computing and Communication written by Mrutyunjaya Panda and published by Springer Nature. This book was released on 2022-12-20 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the papers presented at the First International Conference on Innovations in Intelligent Computing and Communication, ICIICC 2021, held in Bhubaneswar, Odisha, India, in December, 2022. The 31 full papers presented were thoroughly reviewed and selected from 78 submissions. They are divided in three tracks with the following topics: ​Intelligent Computing; Communications; and Machine Learning and Data Analytics.

Research Anthology on Bioinformatics, Genomics, and Computational Biology

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Author :
Publisher : IGI Global
ISBN 13 :
Total Pages : 1509 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Research Anthology on Bioinformatics, Genomics, and Computational Biology by : Management Association, Information Resources

Download or read book Research Anthology on Bioinformatics, Genomics, and Computational Biology written by Management Association, Information Resources and published by IGI Global. This book was released on 2024-03-19 with total page 1509 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the evolving environment of bioinformatics, genomics, and computational biology, academic scholars are facing a challenging challenge – keeping informed about the latest research trends and findings. With unprecedented advancements in sequencing technologies, computational algorithms, and machine learning, these fields have become indispensable tools for drug discovery, disease research, genome sequencing, and more. As scholars strive to decode the language of DNA, predict protein structures, and navigate the complexities of biological data analysis, the need for a comprehensive and up-to-date resource becomes paramount. The Research Anthology on Bioinformatics, Genomics, and Computational Biology is a collection of a carefully curated selection of chapters that serves as the solution to the pressing challenge of keeping pace with the dynamic advancements in these critical disciplines. This anthology is designed to address the informational gap by providing scholars with a consolidated and authoritative source that sheds light on critical issues, innovative theories, and transformative developments in the field. It acts as a single reference point, offering insights into conceptual, methodological, technical, and managerial issues while also providing a glimpse into emerging trends and future opportunities.

Handbook of Deep Learning Applications

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Author :
Publisher : Springer
ISBN 13 : 3030114791
Total Pages : 380 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Handbook of Deep Learning Applications by : Valentina Emilia Balas

Download or read book Handbook of Deep Learning Applications written by Valentina Emilia Balas and published by Springer. This book was released on 2019-02-25 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.