Deep Learning And Parallel Computing Environment For Bioengineering Systems

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Deep Learning and Parallel Computing Environment for Bioengineering Systems

Author : Arun Kumar Sangaiah
Publisher : Academic Press
ISBN 13 : 0128172932
Total Pages : 280 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Deep Learning and Parallel Computing Environment for Bioengineering Systems by : Arun Kumar Sangaiah

Download or read book Deep Learning and Parallel Computing Environment for Bioengineering Systems written by Arun Kumar Sangaiah and published by Academic Press. This book was released on 2019-07-26 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : SOHARA BANU A R
Publisher : MileStone Research Publications
ISBN 13 : 9359149780
Total Pages : 101 pages
Book Rating : 4.3/5 (591 download)

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Book Synopsis Advanced Machine Learning using Python Programming by : SOHARA BANU A R

Download or read book Advanced Machine Learning using Python Programming written by SOHARA BANU A R and published by MileStone Research Publications. This book was released on 2023-07-13 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Mousumi Gupta
Publisher : Springer Nature
ISBN 13 : 9811901511
Total Pages : 474 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Artificial Intelligence on Medical Data by : Mousumi Gupta

Download or read book Artificial Intelligence on Medical Data written by Mousumi Gupta and published by Springer Nature. This book was released on 2022-07-23 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Neha Sharma
Publisher : CRC Press
ISBN 13 : 1040114903
Total Pages : 329 pages
Book Rating : 4.0/5 (41 download)

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Book Synopsis Artificial Intelligence Technology in Healthcare by : Neha Sharma

Download or read book Artificial Intelligence Technology in Healthcare written by Neha Sharma and published by CRC Press. This book was released on 2024-09-05 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Sujata Dash
Publisher : CRC Press
ISBN 13 : 1000534006
Total Pages : 382 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Deep Learning, Machine Learning and IoT in Biomedical and Health Informatics by : Sujata Dash

Download or read book Deep Learning, Machine Learning and IoT in Biomedical and Health Informatics written by Sujata Dash and published by CRC Press. This book was released on 2022-02-10 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Soft Computing for Intelligent Systems

Author : Nikhil Marriwala
Publisher : Springer Nature
ISBN 13 : 9811610487
Total Pages : 653 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Soft Computing for Intelligent Systems by : Nikhil Marriwala

Download or read book Soft Computing for Intelligent Systems written by Nikhil Marriwala and published by Springer Nature. This book was released on 2021-06-22 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents high-quality research papers presented at the International Conference on Soft Computing for Intelligent Systems (SCIS 2020), held during 18–20 December 2020 at University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, Haryana, India. The book encompasses all branches of artificial intelligence, computational sciences and machine learning which is based on computation at some level such as AI-based Internet of things, sensor networks, robotics, intelligent diabetic retinopathy, intelligent cancer genes analysis using computer vision, evolutionary algorithms, fuzzy systems, medical automatic identification intelligence system and applications in agriculture, health care, smart grid and instrumentation systems. The book is helpful for educators, researchers and developers working in the area of recent advances and upcoming technologies utilizing computational sciences in signal processing, imaging, computing, instrumentation, artificial intelligence and their applications.

Lecture Notes in Data Engineering, Computational Intelligence, and Decision Making

Author : Sergii Babichev
Publisher : Springer Nature
ISBN 13 : 303116203X
Total Pages : 735 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Lecture Notes in Data Engineering, Computational Intelligence, and Decision Making by : Sergii Babichev

Download or read book Lecture Notes in Data Engineering, Computational Intelligence, and Decision Making written by Sergii Babichev and published by Springer Nature. This book was released on 2022-09-13 with total page 735 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains of 39 scientific papers which include the results of research regarding the current directions in the fields of data mining, machine learning and decision-making. This book is devoted to current problems of artificial and computational intelligence including decision-making systems. Collecting, analysis and processing information are the current directions of modern computer science. Development of new modern information and computer technologies for data analysis and processing in various fields of data mining and machine learning create the conditions for increasing effectiveness of the information processing by both the decrease of time and the increase of accuracy of the data processing. The papers are divided in terms of their topic into three sections. The first section "Analysis and Modeling of Hybrid Systems and Processes" contains of 11 papers, and the second section "Theoretical and Applied Aspects of Decision-Making Systems" contains of 11 ones too. There are 17 papers in the third section "Data Engineering, Computational Intelligence and Inductive Modeling". The book is focused to scientists and developers in the fields of data mining, machine learning and decision-making systems.

Reinforcement Learning - Principles, Concepts and Applications

Author : Bhavatarini N
Publisher : MileStone Research Publications
ISBN 13 : 9360130087
Total Pages : 144 pages
Book Rating : 4.3/5 (61 download)

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Book Synopsis Reinforcement Learning - Principles, Concepts and Applications by : Bhavatarini N

Download or read book Reinforcement Learning - Principles, Concepts and Applications written by Bhavatarini N and published by MileStone Research Publications. This book was released on 2024-03-25 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reinforcement learning (RL) is a subfield of machine learning that deals with how an agent should learn to take actions in an environment to maximize some notion of cumulative reward. In other words, reinforcement learning is a learning paradigm where an agent learns to interact with an environment by taking actions and observing the feedback it receives in the form of rewards or penalties. It is a feedback-based Machine learning technique in which an agent learns to behave in an environment by performing the actions and seeing the results of actions. For each good action, the agent gets positive feedback, and for each bad action, the agent gets negative feedback or penalty.

Deep Learning and Big Data for Intelligent Transportation

Author : Khaled R. Ahmed
Publisher : Springer Nature
ISBN 13 : 3030656616
Total Pages : 264 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Deep Learning and Big Data for Intelligent Transportation by : Khaled R. Ahmed

Download or read book Deep Learning and Big Data for Intelligent Transportation written by Khaled R. Ahmed and published by Springer Nature. This book was released on 2021-04-10 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contributes to the progress towards intelligent transportation. It emphasizes new data management and machine learning approaches such as big data, deep learning and reinforcement learning. Deep learning and big data are very energetic and vital research topics of today’s technology. Road sensors, UAVs, GPS, CCTV and incident reports are sources of massive amount of data which are crucial to make serious traffic decisions. Herewith this substantial volume and velocity of data, it is challenging to build reliable prediction models based on machine learning methods and traditional relational database. Therefore, this book includes recent research works on big data, deep convolution networks and IoT-based smart solutions to limit the vehicle’s speed in a particular region, to support autonomous safe driving and to detect animals on roads for mitigating animal-vehicle accidents. This book serves broad readers including researchers, academicians, students and working professional in vehicles manufacturing, health and transportation departments and networking companies.

Deep Learning Applications in Medical Imaging

Author : Saxena, Sanjay
Publisher : IGI Global
ISBN 13 : 1799850722
Total Pages : 274 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Deep Learning Applications in Medical Imaging by : Saxena, Sanjay

Download or read book Deep Learning Applications in Medical Imaging written by Saxena, Sanjay and published by IGI Global. This book was released on 2020-10-16 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Before the modern age of medicine, the chance of surviving a terminal disease such as cancer was minimal at best. After embracing the age of computer-aided medical analysis technologies, however, detecting and preventing individuals from contracting a variety of life-threatening diseases has led to a greater survival percentage and increased the development of algorithmic technologies in healthcare. Deep Learning Applications in Medical Imaging is a pivotal reference source that provides vital research on the application of generating pictorial depictions of the interior of a body for medical intervention and clinical analysis. While highlighting topics such as artificial neural networks, disease prediction, and healthcare analysis, this publication explores image acquisition and pattern recognition as well as the methods of treatment and care. This book is ideally designed for diagnosticians, medical imaging specialists, healthcare professionals, physicians, medical researchers, academicians, and students.

Applications of Big Data in Large- and Small-Scale Systems

Author : Goundar, Sam
Publisher : IGI Global
ISBN 13 : 1799866750
Total Pages : 377 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Applications of Big Data in Large- and Small-Scale Systems by : Goundar, Sam

Download or read book Applications of Big Data in Large- and Small-Scale Systems written by Goundar, Sam and published by IGI Global. This book was released on 2021-01-15 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems.

Database Management Systems

Author : Thanuja K
Publisher : MileStone Research Publications
ISBN 13 : 9357374779
Total Pages : 236 pages
Book Rating : 4.3/5 (573 download)

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Book Synopsis Database Management Systems by : Thanuja K

Download or read book Database Management Systems written by Thanuja K and published by MileStone Research Publications. This book was released on 2022-10-21 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Database management courses introduce students to languages, applications and programming used for the design and maintenance of business databases. One of the basic skills covered in database management courses is the use of Structured Query Language (SQL), the most common database manipulation language. Students learn to write programs with packages, debugging procedures, triggers and database structures using SQL. Database management courses may also cover Visual Basic programming language skills for program design. Other database management skills include the use of data and object modeling, relational algebra, relational data models and applications programming. The physical characteristics of databases, reliability and system performance are additional topics in database management. In database concepts classes, the emphasis is on normalization, data dictionaries and data integrity. Students' skill set upon course completion should include designing and implementing normalized databases using database reports and creating forms and tables. Students completing database applications classes will have the skills necessary to create multiple table systems with screens, updates and reports.

Applying Machine Learning Techniques to Bioinformatics: Few-Shot and Zero-Shot Methods

Author : Lilhore, Umesh Kumar
Publisher : IGI Global
ISBN 13 :
Total Pages : 418 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Applying Machine Learning Techniques to Bioinformatics: Few-Shot and Zero-Shot Methods by : Lilhore, Umesh Kumar

Download or read book Applying Machine Learning Techniques to Bioinformatics: Few-Shot and Zero-Shot Methods written by Lilhore, Umesh Kumar and published by IGI Global. This book was released on 2024-03-22 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Why are cutting-edge data science techniques such as bioinformatics, few-shot learning, and zero-shot learning underutilized in the world of biological sciences?. In a rapidly advancing field, the failure to harness the full potential of these disciplines limits scientists ability to unlock critical insights into biological systems, personalized medicine, and biomarker identification. This untapped potential hinders progress and limits our capacity to tackle complex biological challenges. The solution to this issue lies within the pages of Applying Machine Learning Techniques to Bioinformatics. This book serves as a powerful resource, offering a comprehensive analysis of how these emerging disciplines can be effectively applied to the realm of biological research. By addressing these challenges and providing in-depth case studies and practical implementations, the book equips researchers, scientists, and curious minds with the knowledge and techniques needed to navigate the ever-changing landscape of bioinformatics and machine learning within the biological sciences.

Optimization Methods for Product and System Design

Author : Anand J. Kulkarni
Publisher : Springer Nature
ISBN 13 : 981991521X
Total Pages : 266 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Optimization Methods for Product and System Design by : Anand J. Kulkarni

Download or read book Optimization Methods for Product and System Design written by Anand J. Kulkarni and published by Springer Nature. This book was released on 2023-06-11 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book provides a platform to discuss the state-of-the-art developments associated with traditional and advanced single-/multi-objective criteria optimization methods for addressing problems of performance enhancement of the products and systems design. The book in detail discusses the core ideas, underlying principles, mathematical formulations, critical reviews and experimentations, and solutions to complex problems from within the domains such as mechanical engineering design and manufacturing, fault detection and diagnosis, control systems, financial systems, machine learning in medical image processing as well as problems from operations research domain. It will serve as a valuable reference to academicians and industry practitioners involved in improving the efficiency, cost, performance, and durability of the products and systems. The chapters in this book may further give impetus to explore new avenues leading towards multidisciplinary research discussions associated with the resilience and sustainability of the existing systems.

Current Applications of Deep Learning in Cancer Diagnostics

Author : Jyotismita Chaki
Publisher : CRC Press
ISBN 13 : 1000836150
Total Pages : 189 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis Current Applications of Deep Learning in Cancer Diagnostics by : Jyotismita Chaki

Download or read book Current Applications of Deep Learning in Cancer Diagnostics written by Jyotismita Chaki and published by CRC Press. This book was released on 2023-02-22 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines deep learning-based approaches in the field of cancer diagnostics, as well as pre-processing techniques, which are essential to cancer diagnostics. Topics include introduction to current applications of deep learning in cancer diagnostics, pre-processing of cancer data using deep learning, review of deep learning techniques in oncology, overview of advanced deep learning techniques in cancer diagnostics, prediction of cancer susceptibility using deep learning techniques, prediction of cancer reoccurrence using deep learning techniques, deep learning techniques to predict the grading of human cancer, different human cancer detection using deep learning techniques, prediction of cancer survival using deep learning techniques, complexity in the use of deep learning in cancer diagnostics, and challenges and future scopes of deep learning techniques in oncology.

Handbook of Deep Learning in Biomedical Engineering and Health Informatics

Author : E. Golden Julie
Publisher : CRC Press
ISBN 13 : 1000370453
Total Pages : 344 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Handbook of Deep Learning in Biomedical Engineering and Health Informatics by : E. Golden Julie

Download or read book Handbook of Deep Learning in Biomedical Engineering and Health Informatics written by E. Golden Julie and published by CRC Press. This book was released on 2021-09-22 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new volume discusses state-of-the-art deep learning techniques and approaches that can be applied in biomedical systems and health informatics. Deep learning in the biomedical field is an effective method of collecting and analyzing data that can be used for the accurate diagnosis of disease. This volume delves into a variety of applications, techniques, algorithms, platforms, and tools used in this area, such as image segmentation, classification, registration, and computer-aided analysis. The editors proceed on the principle that accurate diagnosis of disease depends on image acquisition and interpretation. There are many methods to get high resolution radiological images, but we are still lacking in automated image interpretation. Currently deep learning techniques are providing a feasible solution for automatic diagnosis of disease with good accuracy. Analyzing clinical data using deep learning techniques enables clinicians to diagnose diseases at an early stage and treat patients more effectively. Chapters explore such approaches as deep learning algorithms, convolutional neural networks and recurrent neural network architecture, image stitching techniques, deep RNN architectures, and more. This volume also depicts how deep learning techniques can be applied for medical diagnostics of several specific health scenarios, such as cancer, COVID-19, acute neurocutaneous syndrome, cardiovascular and neuro diseases, skin lesions and skin cancer, etc. Key features: Introduces important recent technological advancements in the field Describes the various techniques, platforms, and tools used in biomedical deep learning systems Includes informative case studies that help to explain the new technologies Handbook of Deep Learning in Biomedical Engineering and Health Informatics provides a thorough exploration of biomedical systems applied with deep learning techniques and will provide valuable information for researchers, medical and industry practitioners, academicians, and students.

Computational Intelligence in Healthcare

Author : Amit Kumar Manocha
Publisher : Springer Nature
ISBN 13 : 3030687236
Total Pages : 418 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Computational Intelligence in Healthcare by : Amit Kumar Manocha

Download or read book Computational Intelligence in Healthcare written by Amit Kumar Manocha and published by Springer Nature. This book was released on 2021-05-11 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligent systems, which offer great improvement in healthcare sector assisted by machine learning, wireless communications, data analytics, cognitive computing, and mobile computing provide more intelligent and convenient solutions and services. With the help of the advanced techniques, now a days it is possible to understand human body and to handle & process the health data anytime and anywhere. It is a smart healthcare system which includes patient, hospital management, doctors, monitoring, diagnosis, decision making modules, disease prevention to meet the challenges and problems arises in healthcare industry. Furthermore, the advanced healthcare systems need to upgrade with new capabilities to provide human with more intelligent and professional healthcare services to further improve the quality of service and user experience. To explore recent advances and disseminate state-of-the-art techniques related to intelligent healthcare services and applications. This edited book involved in designing systems that will permit the societal acceptance of ambient intelligence including signal processing, imaging, computing, instrumentation, artificial intelligence, internet of health things, data analytics, disease detection, telemedicine, and their applications. As the book includes recent trends in research issues and applications, the contents will be beneficial to Professors, researchers, and engineers. This book will provide support and aid to the researchers involved in designing latest advancements in communication and intelligent systems that will permit the societal acceptance of ambient intelligence. This book presents the latest research being conducted on diverse topics in intelligence technologies with the goal of advancing knowledge and applications healthcare sector and to present the latest snapshot of the ongoing research as well as to shed further light on future directions in this space. The aim of publishing the book is to serve for educators, researchers, and developers working in recent advances and upcoming technologies utilizing computational sciences.