Deep Learning and Parallel Computing Environment for Bioengineering Systems

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Release : 2019-07-26
Genre : Computers
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Book Rating : 932/5 ( reviews)

Deep Learning and Parallel Computing Environment for Bioengineering Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Deep Learning and Parallel Computing Environment for Bioengineering Systems write by Arun Kumar Sangaiah. This book was released on 2019-07-26. Deep Learning and Parallel Computing Environment for Bioengineering Systems available in PDF, EPUB and Kindle. Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, mining, recommendation systems, image processing, pattern recognition and predictions using deep learning paradigms is the major strength of this book. This book integrates the core ideas of deep learning and its applications in bio engineering application domains, to be accessible to all scholars and academicians. The proposed techniques and concepts in this book can be extended in future to accommodate changing business organizations’ needs as well as practitioners’ innovative ideas. Presents novel, in-depth research contributions from a methodological/application perspective in understanding the fusion of deep machine learning paradigms and their capabilities in solving a diverse range of problems Illustrates the state-of-the-art and recent developments in the new theories and applications of deep learning approaches applied to parallel computing environment in bioengineering systems Provides concepts and technologies that are successfully used in the implementation of today's intelligent data-centric critical systems and multi-media Cloud-Big data

Advanced Machine Learning using Python Programming

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Release : 2023-07-13
Genre : Computers
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Book Rating : 780/5 ( reviews)

Advanced Machine Learning using Python Programming - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Advanced Machine Learning using Python Programming write by SOHARA BANU A R. This book was released on 2023-07-13. Advanced Machine Learning using Python Programming available in PDF, EPUB and Kindle. THE AUTHOR(S) AND PUBLISHER OF THIS BOOK HAVE USED THEIR BEST EFFORTS IN PREPARING THIS BOOK. THESE EFFORTS INCLUDE THE DEVELOPMENT, RESEARCH ANDTESTING OF THE THEORIES AND PROGRAMS TO DETERMINE THEIR EFFECTIVENESS. THE AUTHORS AND PUBLISHER MAKES NO WARRANTY OF ANY KIND, EXPRESSED OR IMPLIEDWITH REGARD TO THESE PROGRAMS OR THE DOCUMENTATION CONTAINED IN THIS BOOK. THE AUTHORS AND PUBLISHER SHALL NOT BE LIABLE IN ANY EVENT FORINCIDENTAL OR CONSEQUENTIAL DAMAGES IN CONNECTION WITH, OR ARISING OUT OF, THE FURNISHING, PERFORMANCE, OR USE OF THESE PROGRAMS. COPYRIGHTS © 2023 BY MILESTONE RESEARCH PUBLICATIONS, INC. THIS EDITION IS PUBLISHED BY ARRANGEMENT WITH MILESTONE RESEARCH FOUNDATION, INC. THIS BOOK IS SOLD SUBJECT TO THE CONDITION THAT IT SHALL NOT, BY WAY OF TRADE OR OTHERWISE, BE LENT, RESOLD, HIRED OUT, OR OTHERWISE CIRCULATED WITHOUTTHE PUBLISHER'S PRIOR WRITTEN CONSENT IN ANY FORM OF BINDING OR COVER OTHER THAN THAT IN WHICH IT IS PUBLISHED AND WITHOUT A SIMILAR CONDITIONINCLUDING THIS CONDITION BEING IMPOSED ON THE SUBSEQUENT PURCHASER AND WITHOUT LIMITING THE RIGHTS UNDER COPYRIGHT RESERVED ABOVE, NO PART OF THISPUBLICATION MAY BE REPRODUCED, STORED IN OR INTRODUCED INTO RETRIEVAL SYSTEM, OR TRANSMITTED IN ANY FORM OR BY ANY MEANS (ELECTRONIC, MECHANICAL,PHOTOCOPYING, RECORDING AND OTHERWISE) WITHOUT THE PRIOR WRITTEN PERMISSION OF BOTH THE COPYRIGHT OWNER AND THE ABOVE MENTIONED PUBLISHER OFTHIS BOOK.

Artificial Intelligence on Medical Data

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Release : 2022-07-23
Genre : Technology & Engineering
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Book Rating : 511/5 ( reviews)

Artificial Intelligence on Medical Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Artificial Intelligence on Medical Data write by Mousumi Gupta. This book was released on 2022-07-23. Artificial Intelligence on Medical Data available in PDF, EPUB and Kindle. This book includes high-quality papers presented at the Second International Symposium on Computer Vision and Machine Intelligence in Medical Image Analysis (ISCMM 2021), organized by Computer Applications Department, SMIT in collaboration with Department of Pathology, SMIMS, Sikkim, India, and funded by Indian Council of Medical Research, during 11 – 12 November 2021. It discusses common research problems and challenges in medical image analysis, such as deep learning methods. It also discusses how these theories can be applied to a broad range of application areas, including lung and chest x-ray, breast CAD, microscopy and pathology. The studies included mainly focus on the detection of events from biomedical signals.

Artificial Intelligence Technology in Healthcare

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Release : 2024-09-05
Genre : Technology & Engineering
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Book Rating : 903/5 ( reviews)

Artificial Intelligence Technology in Healthcare - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Artificial Intelligence Technology in Healthcare write by Neha Sharma. This book was released on 2024-09-05. Artificial Intelligence Technology in Healthcare available in PDF, EPUB and Kindle. Artificial Intelligence Technology in Healthcare: Security and Privacy Issues focuses on current issues with patients’ privacy and data security including data breaches in healthcare organizations, unauthorized access to patients’ information, and medical identity theft. It explains recent breakthroughs and problems in deep learning security and privacy issues, emphasizing current state-of-the-art methods, methodologies, implementation, attacks, and countermeasures. It examines the issues related to developing artifiicial intelligence (AI)-based security mechanisms which can gather or share data across several healthcare applications securely and privately. Features: Combines multiple technologies (i.e., Internet of Things [IoT], Federated Computing, and AI) for managing and securing smart healthcare systems. Includes state-of-the-art machine learning, deep learning techniques for predictive analysis, and fog and edge computing-based real-time health monitoring. Covers how to diagnose critical diseases from medical imaging using advanced deep learning-based approaches. Focuses on latest research on privacy, security, and threat detection on COVID-19 through IoT. Illustrates initiatives for research in smart computing for advanced healthcare management systems. This book is aimed at researchers and graduate students in bioengineering, artificial intelligence, and computer engineering.

Deep Learning, Machine Learning and IoT in Biomedical and Health Informatics

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Release : 2022-02-10
Genre : Computers
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Book Rating : 006/5 ( reviews)

Deep Learning, Machine Learning and IoT in Biomedical and Health Informatics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Deep Learning, Machine Learning and IoT in Biomedical and Health Informatics write by Sujata Dash. This book was released on 2022-02-10. Deep Learning, Machine Learning and IoT in Biomedical and Health Informatics available in PDF, EPUB and Kindle. Biomedical and Health Informatics is an important field that brings tremendous opportunities and helps address challenges due to an abundance of available biomedical data. This book examines and demonstrates state-of-the-art approaches for IoT and Machine Learning based biomedical and health related applications. This book aims to provide computational methods for accumulating, updating and changing knowledge in intelligent systems and particularly learning mechanisms that help us to induce knowledge from the data. It is helpful in cases where direct algorithmic solutions are unavailable, there is lack of formal models, or the knowledge about the application domain is inadequately defined. In the future IoT has the impending capability to change the way we work and live. These computing methods also play a significant role in design and optimization in diverse engineering disciplines. With the influence and the development of the IoT concept, the need for AI (artificial intelligence) techniques has become more significant than ever. The aim of these techniques is to accept imprecision, uncertainties and approximations to get a rapid solution. However, recent advancements in representation of intelligent IoTsystems generate a more intelligent and robust system providing a human interpretable, low-cost, and approximate solution. Intelligent IoT systems have demonstrated great performance to a variety of areas including big data analytics, time series, biomedical and health informatics. This book will be very beneficial for the new researchers and practitioners working in the biomedical and healthcare fields to quickly know the best performing methods. It will also be suitable for a wide range of readers who may not be scientists but who are also interested in the practice of such areas as medical image retrieval, brain image segmentation, among others. • Discusses deep learning, IoT, machine learning, and biomedical data analysis with broad coverage of basic scientific applications • Presents deep learning and the tremendous improvement in accuracy, robustness, and cross- language generalizability it has over conventional approaches • Discusses various techniques of IoT systems for healthcare data analytics • Provides state-of-the-art methods of deep learning, machine learning and IoT in biomedical and health informatics • Focuses more on the application of algorithms in various real life biomedical and engineering problems