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Big Data Analytics in Oncology with R by Atanu Bhattacharjee Pdf
"Big Data Analytics in Oncology with R serves the analytical approaches for big data analysis. There is huge progressed in advanced computation with R. But there are several technical challenges faced to work with big data. These challenges are with computational aspect and work with fastest way to get computational results. Clinical decision through genomic information and survival outcomes are now unavoidable in cutting-edge oncology research. This book is intended to provide a comprehensive text to work with some recent development in the area"--
Big Data Analytics in Oncology with R by Atanu Bhattacharjee Pdf
Big Data Analytics in Oncology with R serves the analytical approaches for big data analysis. There is huge progressed in advanced computation with R. But there are several technical challenges faced to work with big data. These challenges are with computational aspect and work with fastest way to get computational results. Clinical decision through genomic information and survival outcomes are now unavoidable in cutting-edge oncology research. This book is intended to provide a comprehensive text to work with some recent development in the area. Features: Covers gene expression data analysis using R and survival analysis using R Includes bayesian in survival-gene expression analysis Discusses competing-gene expression analysis using R Covers Bayesian on survival with omics data This book is aimed primarily at graduates and researchers studying survival analysis or statistical methods in genetics.
Big Data in Oncology: Impact, Challenges, and Risk Assessment by Neeraj Kumar Fuloria,Rishabha Malviya,Swati Verma,Balamurugan Balusamy Pdf
We are in the era of large-scale science. In oncology there is a huge number of data sets grouping information on cancer genomes, transcriptomes, clinical data, and more. The challenge of big data in cancer is to integrate all this diversity of data collected into a unique platform that can be analyzed, leading to the generation of readable files. The possibility of harnessing information from all the accumulated data leads to an improvement in cancer patient treatment and outcome. Solving the big data problem in oncology has multiple facets. Big data in Oncology: Impact, Challenges, and Risk Assessment brings together insights from emerging sophisticated information and communication technologies such as artificial intelligence, data science, and big data analytics for cancer management. This book focuses on targeted disease treatment using big data analytics. It provides information about targeted treatment in oncology, challenges and application of big data in cancer therapy. Recent developments in the fields of artificial intelligence, machine learning, medical imaging, personalized medicine, computing and data analytics for improved patient care. Description of the application of big data with AI to discover new targeting points for cancer treatment. Summary of several risk assessments in the field of oncology using big data. Focus on prediction of doses in oncology using big data The most targeted or relevant audience is academics, research scholars, health care professionals, hospital management, pharmaceutical chemists, the biomedical industry, software engineers and IT professionals.
Research Anthology on Big Data Analytics, Architectures, and Applications by Management Association, Information Resources Pdf
Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.
This book provides a single source of information on three major bioengineering areas: engineering at the cellular and molecular level; biomedical devices / instrument engineering; and data engineering. It explores the latest strategies that are essential to advancing our understanding of the mechanisms of human diseases, the development of new enzyme-based technologies, diagnostics, prosthetics, high-performance computing platforms for managing huge amounts of biological data, and the use of deep learning methods to create predictive models. The book also highlights the growing importance of integrating chemistry into life sciences research, most notably concerning the development and evaluation of nanomaterials and nanoparticles and their interactions with biological material. The underlying interdisciplinary theme of bioengineering is addressed in a range of multifaceted applications and worked out examples provided in each chapter.
Smart and Sustainable Technologies: Rural and Tribal Development Using IoT and Cloud Computing by Srikanta Patnaik,Roumen Kountchev,Vipul Jain Pdf
This book presents a collection of peer-reviewed best selected research papers presented at the First International Conference on Smart and Sustainable Technologies (ICSST 2021), organized by Department of ECE, GIET University, Gunupur, Rayagada, Odisha, India, during December 16–18, 2021. The proceedings of the conference have a special focus on the developments of local tribe and rural people using smart and sustainable technologies. It is an interdisciplinary platform for researchers, practitioners, and educators as well as NGO workers who are working in the area of web engineering, IoT and cloud computing, Internet of Everything, data science, artificial intelligence, machine learning, computer vision, and intelligent robotics, particularly for the rural and tribal development.
Exploratory Data Analytics for Healthcare by R. Lakshmana Kumar,R. Indrakumari,B. Balamurugan,Achyut Shankar Pdf
Exploratory data analysis helps to recognize natural patterns hidden in the data. This book describes the tools for hypothesis generation by visualizing data through graphical representation and provides insight into advanced analytics concepts in an easy way. The book addresses the complete data visualization technologies workflow, explores basic and high-level concepts of computer science and engineering in medical science, and provides an overview of the clinical scientific research areas that enables smart diagnosis equipment. It will discuss techniques and tools used to explore large volumes of medical data and offers case studies that focus on the innovative technological upgradation and challenges faced today. The primary audience for the book includes specialists, researchers, graduates, designers, experts, physicians, and engineers who are doing research in this domain.
Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics by R. Sujatha,S. L. Aarthy,R. Vettriselvan Pdf
Data science revolves around two giants: Big Data analytics and Deep Learning. It is becoming challenging to handle and retrieve useful information due to how fast data is expanding. This book presents the technologies and tools to simplify and streamline the formation of Big Data as well as Deep Learning systems. This book discusses how Big Data and Deep Learning hold the potential to significantly increase data understanding and decision-making. It also covers numerous applications in healthcare, education, communication, media, and entertainment. Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics offers innovative platforms for integrating Big Data and Deep Learning and presents issues related to adequate data storage, semantic indexing, data tagging, and fast information retrieval. FEATURES Provides insight into the skill set that leverages one’s strength to act as a good data analyst Discusses how Big Data and Deep Learning hold the potential to significantly increase data understanding and help in decision-making Covers numerous potential applications in healthcare, education, communication, media, and entertainment Offers innovative platforms for integrating Big Data and Deep Learning Presents issues related to adequate data storage, semantic indexing, data tagging, and fast information retrieval from Big Data This book is aimed at industry professionals, academics, research scholars, system modelers, and simulation experts.
AIoT and Big Data Analytics for Smart Healthcare Applications by Shreyas Suresh Rao, Steven Lawrence Fernandes, Chandra Singh, Rathishchandra R. Gatti, Harisha A., Rohanchandra R. Gatty Pdf
AIoT (Artificial Intelligence of Things) and Big Data Analytics are catalyzing a healthcare revolution. This book is an accessible volume that summarizes the information available. In this book, researchers explore how AIoT and Big Data can seamlessly integrate into healthcare, enhancing medical services and devices while adhering to established protocols. The book demonstrates the crucial role of these technologies during healthcare crises like the COVID-19 pandemic. It presents novel solutions and computational techniques powered by AIoT, Machine Learning, and Deep Learning, providing a new frontier in healthcare problem-solving. Key Features: Real-Life Illustrations: Real-world examples showcase AIoT and Big Data in action, highlighting their impact in healthcare. Comprehensive Exploration: The book offers a thorough examination of AIoT, Big Data, and their harmonious synergy within the healthcare landscape. Visual Aids: Complex concepts become approachable through diagrams, flowcharts, and infographics, making technical processes and system designs more digestible. Ethical Insights: Delving into the ethical dimensions of AIoT and Big Data, it addresses concerns like data bias, patient consent, and transparency in healthcare. Forward-Looking Discourse: The book engages with emerging trends, potential innovations, and the future direction of AIoT and Big Data, making it a compass for healthcare transformation. Researchers, whether from academia, industry, or research and development organizations, interested in AIoT, Big Data, artificial intelligence, and healthcare optimization, will find this book informative. It also serves as an update for tech enthusiasts who want to explore the future of healthcare powered by AI and data.
Big Data Analytics in Chemoinformatics and Bioinformatics by Subhash C. Basak,Marjan Vračko Pdf
Big Data Analytics in Chemoinformatics and Bioinformatics: With Applications to Computer-Aided Drug Design, Cancer Biology, Emerging Pathogens and Computational Toxicology provides an up-to-date presentation of big data analytics methods and their applications in diverse fields. The proper management of big data for decision-making in scientific and social issues is of paramount importance. This book gives researchers the tools they need to solve big data problems in these fields. It begins with a section on general topics that all readers will find useful and continues with specific sections covering a range of interdisciplinary applications. Here, an international team of leading experts review their respective fields and present their latest research findings, with case studies used throughout to analyze and present key information. Brings together the current knowledge on the most important aspects of big data, including analysis using deep learning and fuzzy logic, transparency and data protection, disparate data analytics, and scalability of the big data domain Covers many applications of big data analysis in diverse fields such as chemistry, chemoinformatics, bioinformatics, computer-assisted drug/vaccine design, characterization of emerging pathogens, and environmental protection Highlights the considerable benefits offered by big data analytics to science, in biomedical fields and in industry
Data Engineering and Data Science by Kukatlapalli Pradeep Kumar,Aynur Unal,Vinay Jha Pillai,Hari Murthy,M. Niranjanamurthy Pdf
DATA ENGINEERING and DATA SCIENCE Written and edited by one of the most prolific and well-known experts in the field and his team, this exciting new volume is the “one-stop shop” for the concepts and applications of data science and engineering for data scientists across many industries. The field of data science is incredibly broad, encompassing everything from cleaning data to deploying predictive models. However, it is rare for any single data scientist to be working across the spectrum day to day. Data scientists usually focus on a few areas and are complemented by a team of other scientists and analysts. Data engineering is also a broad field, but any individual data engineer doesn’t need to know the whole spectrum of skills. Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. For all the work that data scientists do to answer questions using large sets of information, there have to be mechanisms for collecting and validating that information. In this exciting new volume, the team of editors and contributors sketch the broad outlines of data engineering, then walk through more specific descriptions that illustrate specific data engineering roles. Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This book brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.
Big Data Analytics and Intelligent Techniques for Smart Cities by Kolla Bhanu Prakash,Janmenjoy Nayak,B Madhhav,Sanjeevikumar Padmanaban,Valentina Emilia Balas Pdf
Big Data Analytics and Intelligent Techniques for Smart Cities covers fundamentals, advanced concepts, and applications of big data analytics for smart cities in a single volume. This comprehensive reference text discusses big data theory modeling and simulation for smart cities and examines case studies in a single volume. The text discusses how to develop a smart city and state-of-the-art system design, system verification, real-time control and adaptation, Internet of Things, and testbeds. It covers applications of smart cities as they relate to smart transportation/connected vehicle (CV) and intelligent transportation systems (ITS) for improved mobility, safety, and environmental protection. It will be useful as a reference text for graduate students in different areas including electrical engineering, computer science engineering, civil engineering, and electronics and communications engineering. Features: Technologies and algorithms associated with the application of big data for smart cities Discussions on big data theory modeling and simulation for smart cities Applications of smart cities as they relate to smart transportation and intelligent transportation systems (ITS) Discussions on concepts including smart education, smart culture, and smart transformation management for social and societal changes
Akash Kumar Bhoi,Ranjit Panigrahi,Victor, Hugo C. de Albuquerque,Rutvij H. Jhaveri
Author : Akash Kumar Bhoi,Ranjit Panigrahi,Victor, Hugo C. de Albuquerque,Rutvij H. Jhaveri Publisher : Walter de Gruyter GmbH & Co KG Page : 354 pages File Size : 51,9 Mb Release : 2024-03-18 Category : Computers ISBN : 9783110750942
Healthcare Big Data Analytics by Akash Kumar Bhoi,Ranjit Panigrahi,Victor, Hugo C. de Albuquerque,Rutvij H. Jhaveri Pdf
This book highlights how optimized big data applications can be used for patient monitoring and clinical diagnosis. In fact, IoT-based applications are data-driven and mostly employ modern optimization techniques. The book also explores challenges, opportunities, and future research directions, discussing the stages of data collection and pre-processing, as well as the associated challenges and issues in data handling and setup.
Transforming Management with AI, Big-Data, and IoT by Fadi Al-Turjman,Satya Prakash Yadav,Manoj Kumar,Vibhash Yadav,Thompson Stephan Pdf
This book discusses the effect that artificial intelligence (AI) and Internet of Things (IoT) have on industry. The authors start by showing how the application of these technologies has already stretched across domains such as law, political science, policy, and economics and how it will soon permeate areas of autonomous transportation, education, and space exploration, only to name a few. The authors then discuss applications in a variety of industries. Throughout the volume, the authors provide detailed, well-illustrated treatments of each topic with abundant examples and exercises. This book provides relevant theoretical frameworks and the latest empirical research findings in various applications. The book is written for professionals who want to improve their understanding of the strategic role of trust at different levels of the information and knowledge society, that is, trust at the level of the global economy, of networks and organizations, of teams and work groups, of information systems and, finally, trust at the level of individuals as actors in the networked environments. Presents research in various industries and how artificial intelligence and Internet of Things is changing the landscape of business and management; Includes new and innovative features in artificial intelligence and IoT that can help in raising economic efficiency at both micro and macro levels; Examines case studies with tried and tested approaches to resolution of typical problems in each application of study.
Emerging Developments and Practices in Oncology by El Naqa, Issam Pdf
Cancer is a leading cause of death that affects numerous people at every age and their relatives. In recent years, there has been a tremendous advancement in imaging and biotechnology technologies and techniques for aiding in the detection, diagnosis, and treatment of cancer. Emerging Developments and Practices in Oncology provides research on recent advances in oncology aiming to improve early detection and personalized treatment of cancer. While highlighting applied methods of therapy, such as body radiotherapy, chemoradiotherapy, and immunotherapy, readers learn about the transforming approach to oncology in modern medicine and new technologies used to diagnose and treat cancer. This book is an important resource for medical trainees, graduate students, active practitioners, researchers, and clinical scientists seeking current research on oncology trends and applications.
