Big Data Analytics In Oncology With R

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Big Data Analytics In Oncology With R
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Author : Atanu Bhattacharjee
language : en
Publisher: CRC Press
Release Date : 2022-12-29
Big Data Analytics In Oncology With R written by Atanu Bhattacharjee and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-29 with Mathematics categories.
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 Analytics In Oncology With R
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Author : Atanu Bhattacharjee
language : en
Publisher: Chapman & Hall/CRC
Release Date : 2023
Big Data Analytics In Oncology With R written by Atanu Bhattacharjee and has been published by Chapman & Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
"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 In Oncology Impact Challenges And Risk Assessment
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Author : Neeraj Kumar Fuloria
language : en
Publisher: CRC Press
Release Date : 2023-12-21
Big Data In Oncology Impact Challenges And Risk Assessment written by Neeraj Kumar Fuloria and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-21 with Medical categories.
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.
Big Data Analytics In Bioinformatics And Healthcare
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Author : Wang, Baoying
language : en
Publisher: IGI Global
Release Date : 2014-10-31
Big Data Analytics In Bioinformatics And Healthcare written by Wang, Baoying and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-31 with Computers categories.
As technology evolves and electronic data becomes more complex, digital medical record management and analysis becomes a challenge. In order to discover patterns and make relevant predictions based on large data sets, researchers and medical professionals must find new methods to analyze and extract relevant health information. Big Data Analytics in Bioinformatics and Healthcare merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management. Complete with interdisciplinary research resources, this publication is an essential reference source for researchers, practitioners, and students interested in the fields of biological computation, database management, and health information technology, with a special focus on the methodologies and tools to manage massive and complex electronic information.
Big Data Analytics In Bioinformatics And Healthcare
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Author : Baoying Wang
language : en
Publisher:
Release Date : 2014-10
Big Data Analytics In Bioinformatics And Healthcare written by Baoying Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10 with Data mining categories.
"This book merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management"--
Comprehensive Energy Systems
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Author : Ibrahim Dincer
language : en
Publisher: Elsevier
Release Date : 2018-02-07
Comprehensive Energy Systems written by Ibrahim Dincer and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-07 with Science categories.
Comprehensive Energy Systems, Seven Volume Set provides a unified source of information covering the entire spectrum of energy, one of the most significant issues humanity has to face. This comprehensive book describes traditional and novel energy systems, from single generation to multi-generation, also covering theory and applications. In addition, it also presents high-level coverage on energy policies, strategies, environmental impacts and sustainable development. No other published work covers such breadth of topics in similar depth. High-level sections include Energy Fundamentals, Energy Materials, Energy Production, Energy Conversion, and Energy Management. Offers the most comprehensive resource available on the topic of energy systems Presents an authoritative resource authored and edited by leading experts in the field Consolidates information currently scattered in publications from different research fields (engineering as well as physics, chemistry, environmental sciences and economics), thus ensuring a common standard and language
Big Data Analytics In Chemoinformatics And Bioinformatics
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Author : Subhash C. Basak
language : en
Publisher: Elsevier
Release Date : 2022-12-06
Big Data Analytics In Chemoinformatics And Bioinformatics written by Subhash C. Basak and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-06 with Science categories.
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
Big Data Analytics In Future Power Systems
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Author : Ahmed F. Zobaa
language : en
Publisher: CRC Press
Release Date : 2018-08-14
Big Data Analytics In Future Power Systems written by Ahmed F. Zobaa and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-14 with Science categories.
Power systems are increasingly collecting large amounts of data due to the expansion of the Internet of Things into power grids. In a smart grids scenario, a huge number of intelligent devices will be connected with almost no human intervention characterizing a machine-to-machine scenario, which is one of the pillars of the Internet of Things. The book characterizes and evaluates how the emerging growth of data in communications networks applied to smart grids will impact the grid efficiency and reliability. Additionally, this book discusses the various security concerns that become manifest with Big Data and expanded communications in power grids. Provide a general description and definition of big data, which has been gaining significant attention in the research community. Introduces a comprehensive overview of big data optimization methods in power system. Reviews the communication devices used in critical infrastructure, especially power systems; security methods available to vet the identity of devices; and general security threats in CI networks. Presents applications in power systems, such as power flow and protection. Reviews electricity theft concerns and the wide variety of data-driven techniques and applications developed for electricity theft detection.
Big Data Analytics For Healthcare
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Author : Pantea Keikhosrokiani
language : en
Publisher: Academic Press
Release Date : 2022-05-19
Big Data Analytics For Healthcare written by Pantea Keikhosrokiani and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-19 with Medical categories.
Big Data Analytics and Medical Information Systems presents the valuable use of artificial intelligence and big data analytics in healthcare and medical sciences. It focuses on theories, methods and approaches in which data analytic techniques can be used to examine medical data to provide a meaningful pattern for classification, diagnosis, treatment, and prediction of diseases. The book discusses topics such as theories and concepts of the field, and how big medical data mining techniques and applications can be applied to classification, diagnosis, treatment, and prediction of diseases. In addition, it covers social, behavioral, and medical fake news analytics to prevent medical misinformation and myths. It is a valuable resource for graduate students, researchers and members of biomedical field who are interested in learning more about analytic tools to support their work. - Presents theories, methods and approaches in which data analytic techniques are used for medical data - Brings practical information on how to use big data for classification, diagnosis, treatment, and prediction of diseases - Discusses social, behavioral, and medical fake news analytics for medical information systems
Integrating Deep Learning Algorithms To Overcome Challenges In Big Data Analytics
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Author : R. Sujatha
language : en
Publisher: CRC Press
Release Date : 2021-09-22
Integrating Deep Learning Algorithms To Overcome Challenges In Big Data Analytics written by R. Sujatha and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-22 with Computers categories.
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.