Trends in Deep Learning Methodologies

Trends in Deep Learning Methodologies
Author: Vincenzo Piuri,Sandeep Raj,Angelo Genovese,Rajshree Srivastava
Publsiher: Academic Press
Total Pages: 306
Release: 2020-11-12
ISBN: 0128232684
Category: Computers
Language: EN, FR, DE, ES & NL

Trends in Deep Learning Methodologies Book Excerpt:

Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models. Provides insights into the theory, algorithms, implementation and the application of deep learning techniques Covers a wide range of applications of deep learning across smart healthcare and smart engineering Investigates the development of new models and how they can be exploited to find appropriate solutions

Trends in Deep Learning Methodologies

Trends in Deep Learning Methodologies
Author: Vincenzo Piuri,Sandeep Raj,Angelo Genovese,Rajshree Srivastava
Publsiher: Academic Press
Total Pages: 306
Release: 2020-11-30
ISBN: 0128222263
Category: Computers
Language: EN, FR, DE, ES & NL

Trends in Deep Learning Methodologies Book Excerpt:

Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models. Provides insights into the theory, algorithms, implementation and the application of deep learning techniques Covers a wide range of applications of deep learning across smart healthcare and smart engineering Investigates the development of new models and how they can be exploited to find appropriate solutions

VLSI and Hardware Implementations using Modern Machine Learning Methods

VLSI and Hardware Implementations using Modern Machine Learning Methods
Author: Sandeep Saini,Kusum Lata,G.R. Sinha
Publsiher: CRC Press
Total Pages: 328
Release: 2021-12-31
ISBN: 1000523810
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

VLSI and Hardware Implementations using Modern Machine Learning Methods Book Excerpt:

Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learning–based methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques. Features: Provides the details of state-of-the-art machine learning methods used in VLSI design Discusses hardware implementation and device modeling pertaining to machine learning algorithms Explores machine learning for various VLSI architectures and reconfigurable computing Illustrates the latest techniques for device size and feature optimization Highlights the latest case studies and reviews of the methods used for hardware implementation This book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.

Handbook of Research on Machine Learning Applications and Trends Algorithms Methods and Techniques

Handbook of Research on Machine Learning Applications and Trends  Algorithms  Methods  and Techniques
Author: Olivas, Emilio Soria,Guerrero, Jos‚ David Mart¡n,Martinez-Sober, Marcelino,Magdalena-Benedito, Jose Rafael,Serrano L¢pez, Antonio Jos‚
Publsiher: IGI Global
Total Pages: 852
Release: 2009-08-31
ISBN: 1605667676
Category: Computers
Language: EN, FR, DE, ES & NL

Handbook of Research on Machine Learning Applications and Trends Algorithms Methods and Techniques Book Excerpt:

"This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.

Deep Learning for Personalized Healthcare Services

Deep Learning for Personalized Healthcare Services
Author: Vishal Jain,Jyotir Moy Chatterjee,Hadi Hedayati,Salahddine Krit,Omer Deperlioglu
Publsiher: Walter de Gruyter GmbH & Co KG
Total Pages: 268
Release: 2021-10-25
ISBN: 3110708124
Category: Computers
Language: EN, FR, DE, ES & NL

Deep Learning for Personalized Healthcare Services Book Excerpt:

This book uncovers the stakes and possibilities involved in realising personalised healthcare services through efficient and effective deep learning algorithms, enabling the healthcare industry to develop meaningful and cost-effective services. This requires effective understanding, application and amalgamation of deep learning with several other computing technologies, such as machine learning, data mining, and natural language processing.

Proceedings of International Conference on Recent Trends in Machine Learning IoT Smart Cities and Applications

Proceedings of International Conference on Recent Trends in Machine Learning  IoT  Smart Cities and Applications
Author: Vinit Kumar Gunjan,Jacek M. Zurada
Publsiher: Springer Nature
Total Pages: 998
Release: 2020-10-17
ISBN: 9811572348
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Proceedings of International Conference on Recent Trends in Machine Learning IoT Smart Cities and Applications Book Excerpt:

This book gathers selected research papers presented at the International Conference on Recent Trends in Machine Learning, IOT, Smart Cities & Applications (ICMISC 2020), held on 29–30 March 2020 at CMR Institute of Technology, Hyderabad, Telangana, India. Discussing current trends in machine learning, Internet of things, and smart cities applications, with a focus on multi-disciplinary research in the area of artificial intelligence and cyber-physical systems, this book is a valuable resource for scientists, research scholars and PG students wanting formulate their research ideas and find the future directions in these areas. Further, it serves as a reference work anyone wishing to understand the latest technologies used by practicing engineers around the globe.

Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems

Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems
Author: K. Suganthi,R. Karthik,G. Rajesh,Peter Ho Chiung Ching
Publsiher: CRC Press
Total Pages: 296
Release: 2021-09-14
ISBN: 1000441814
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems Book Excerpt:

This book offers the latest advances and results in the fields of Machine Learning and Deep Learning for Wireless Communication and provides positive and critical discussions on the challenges and prospects. It provides a broad spectrum in understanding the improvements in Machine Learning and Deep Learning that are motivating by the specific constraints posed by wireless networking systems. The book offers an extensive overview on intelligent Wireless Communication systems and its underlying technologies, research challenges, solutions, and case studies. It provides information on intelligent wireless communication systems and its models, algorithms and applications. The book is written as a reference that offers the latest technologies and research results to various industry problems.

Research Anthology on Machine Learning Techniques Methods and Applications

Research Anthology on Machine Learning Techniques  Methods  and Applications
Author: Management Association, Information Resources
Publsiher: IGI Global
Total Pages: 1516
Release: 2022-05-13
ISBN: 1668462923
Category: Computers
Language: EN, FR, DE, ES & NL

Research Anthology on Machine Learning Techniques Methods and Applications Book Excerpt:

Machine learning continues to have myriad applications across industries and fields. To ensure this technology is utilized appropriately and to its full potential, organizations must better understand exactly how and where it can be adapted. Further study on the applications of machine learning is required to discover its best practices, challenges, and strategies. The Research Anthology on Machine Learning Techniques, Methods, and Applications provides a thorough consideration of the innovative and emerging research within the area of machine learning. The book discusses how the technology has been used in the past as well as potential ways it can be used in the future to ensure industries continue to develop and grow. Covering a range of topics such as artificial intelligence, deep learning, cybersecurity, and robotics, this major reference work is ideal for computer scientists, managers, researchers, scholars, practitioners, academicians, instructors, and students.

Machine Learning Techniques for Smart City Applications Trends and Solutions

Machine Learning Techniques for Smart City Applications  Trends and Solutions
Author: D. Jude Hemanth
Publsiher: Springer Nature
Total Pages: 227
Release: 2022-10-21
ISBN: 303108859X
Category: Computers
Language: EN, FR, DE, ES & NL

Machine Learning Techniques for Smart City Applications Trends and Solutions Book Excerpt:

This book discusses the application of different machine learning techniques to the sub-concepts of smart cities such as smart energy, transportation, waste management, health, infrastructure, etc. The focus of this book is to come up with innovative solutions in the above-mentioned issues with the purpose of alleviating the pressing needs of human society. This book includes content with practical examples which are easy to understand for readers. It also covers a multi-disciplinary field and, consequently, it benefits a wide readership including academics, researchers, and practitioners.

Trends and Applications of Text Summarization Techniques

Trends and Applications of Text Summarization Techniques
Author: Fiori, Alessandro
Publsiher: IGI Global
Total Pages: 335
Release: 2019-08-30
ISBN: 1522593756
Category: Computers
Language: EN, FR, DE, ES & NL

Trends and Applications of Text Summarization Techniques Book Excerpt:

While the availability of electronic documents increases exponentially with advancing technology, the time spent to process this wealth of resourceful information decreases. Content analysis and information extraction must be aided by summarization methods to quickly parcel pieces of interest and allow for succinct user familiarization in a simple, efficient manner. Trends and Applications of Text Summarization Techniques is a pivotal reference source that explores the latest approaches of document summarization including update, multi-lingual, and domain-oriented summarization tasks and examines their current real-world applications in multiple fields. Featuring coverage on a wide range of topics such as parallel construction, social network integration, and evaluation metrics, this book is ideally designed for information technology practitioners, computer scientists, bioinformatics analysts, business managers, healthcare professionals, academicians, researchers, and students.

Deep Learning Approaches to Cloud Security

Deep Learning Approaches to Cloud Security
Author: Pramod Singh Rathore,Vishal Dutt,Rashmi Agrawal,Satya Murthy Sasubilli,Srinivasa Rao Swarna
Publsiher: John Wiley & Sons
Total Pages: 308
Release: 2022-01-26
ISBN: 1119760526
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Deep Learning Approaches to Cloud Security Book Excerpt:

DEEP LEARNING APPROACHES TO CLOUD SECURITY Covering one of the most important subjects to our society today, cloud security, this editorial team delves into solutions taken from evolving deep learning approaches, solutions allowing computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts. Deep learning is the fastest growing field in computer science. Deep learning algorithms and techniques are found to be useful in different areas like automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delay in children. However, applying deep learning techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. This book provides state of the art approaches of deep learning in these areas, including areas of detection and prediction, as well as future framework development, building service systems and analytical aspects. In all these topics, deep learning approaches, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. This book is intended for dealing with modeling and performance prediction of the efficient cloud security systems, thereby bringing a newer dimension to this rapidly evolving field. This groundbreaking new volume presents these topics and trends of deep learning, bridging the research gap, and presenting solutions to the challenges facing the engineer or scientist every day in this area. Whether for the veteran engineer or the student, this is a must-have for any library. Deep Learning Approaches to Cloud Security: Is the first volume of its kind to go in-depth on the newest trends and innovations in cloud security through the use of deep learning approaches Covers these important new innovations, such as AI, data mining, and other evolving computing technologies in relation to cloud security Is a useful reference for the veteran computer scientist or engineer working in this area or an engineer new to the area, or a student in this area Discusses not just the practical applications of these technologies, but also the broader concepts and theory behind how these deep learning tools are vital not just to cloud security, but society as a whole Audience: Computer scientists, scientists and engineers working with information technology, design, network security, and manufacturing, researchers in computers, electronics, and electrical and network security, integrated domain, and data analytics, and students in these areas

Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics

Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics
Author: R. Sujatha,S. L. Aarthy,R. Vettriselvan
Publsiher: CRC Press
Total Pages: 216
Release: 2021-09-22
ISBN: 1000454533
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics Book Excerpt:

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.

Explainable Artificial Intelligence for Smart Cities

Explainable Artificial Intelligence for Smart Cities
Author: Mohamed Lahby,Utku Kose,Akash Kumar Bhoi
Publsiher: CRC Press
Total Pages: 360
Release: 2021-11-10
ISBN: 1000472361
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Explainable Artificial Intelligence for Smart Cities Book Excerpt:

Thanks to rapid technological developments in terms of Computational Intelligence, smart tools have been playing active roles in daily life. It is clear that the 21st century has brought about many advantages in using high-level computation and communication solutions to deal with real-world problems; however, more technologies bring more changes to society. In this sense, the concept of smart cities has been a widely discussed topic in terms of society and Artificial Intelligence-oriented research efforts. The rise of smart cities is a transformation of both community and technology use habits, and there are many different research orientations to shape a better future. The objective of this book is to focus on Explainable Artificial Intelligence (XAI) in smart city development. As recently designed, advanced smart systems require intense use of complex computational solutions (i.e., Deep Learning, Big Data, IoT architectures), the mechanisms of these systems become ‘black-box’ to users. As this means that there is no clear clue about what is going on within these systems, anxieties regarding ensuring trustworthy tools also rise. In recent years, attempts have been made to solve this issue with the additional use of XAI methods to improve transparency levels. This book provides a timely, global reference source about cutting-edge research efforts to ensure the XAI factor in smart city-oriented developments. The book includes both positive and negative outcomes, as well as future insights and the societal and technical aspects of XAI-based smart city research efforts. This book contains nineteen contributions beginning with a presentation of the background of XAI techniques and sustainable smart-city applications. It then continues with chapters discussing XAI for Smart Healthcare, Smart Education, Smart Transportation, Smart Environment, Smart Urbanization and Governance, and Cyber Security for Smart Cities.

Artificial Intelligence and Machine Learning Methods in COVID 19 and Related Health Diseases

Artificial Intelligence and Machine Learning Methods in COVID 19 and Related Health Diseases
Author: Victor Chang,Harleen Kaur,Simon James Fong
Publsiher: Springer Nature
Total Pages: 255
Release: 2022-06-28
ISBN: 3031045971
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Artificial Intelligence and Machine Learning Methods in COVID 19 and Related Health Diseases Book Excerpt:

This Springer book provides a perfect platform to submit chapters that discuss the prospective developments and innovative ideas in artificial intelligence and machine learning techniques in the diagnosis of COVID-19. COVID-19 is a huge challenge to humanity and the medical sciences. So far as of today, we have been unable to find a medical solution (Vaccine). However, globally, we are still managing the use of technology for our work, communications, analytics, and predictions with the use of advancement in data science, communication technologies (5G & Internet), and AI. Therefore, we might be able to continue and live safely with the use of research in advancements in data science, AI, machine learning, mobile apps, etc., until we can find a medical solution such as a vaccine. We have selected eleven chapters after the vigorous review process. Each chapter has demonstrated the research contributions and research novelty. Each group of authors must fulfill strict requirements.

Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches

Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches
Author: K. Gayathri Devi,Mamata Rath,Nguyen Thi Dieu Linh
Publsiher: CRC Press
Total Pages: 255
Release: 2020-10-08
ISBN: 1000179532
Category: Computers
Language: EN, FR, DE, ES & NL

Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches Book Excerpt:

Artificial Intelligence (AI), when incorporated with machine learning and deep learning algorithms, has a wide variety of applications today. This book focuses on the implementation of various elementary and advanced approaches in AI that can be used in various domains to solve real-time decision-making problems. The book focuses on concepts and techniques used to run tasks in an automated manner. It discusses computational intelligence in the detection and diagnosis of clinical and biomedical images, covers the automation of a system through machine learning and deep learning approaches, presents data analytics and mining for decision-support applications, and includes case-based reasoning, natural language processing, computer vision, and AI approaches in real-time applications. Academic scientists, researchers, and students in the various domains of computer science engineering, electronics and communication engineering, and information technology, as well as industrial engineers, biomedical engineers, and management, will find this book useful. By the end of this book, you will understand the fundamentals of AI. Various case studies will develop your adaptive thinking to solve real-time AI problems. Features Includes AI-based decision-making approaches Discusses computational intelligence in the detection and diagnosis of clinical and biomedical images Covers automation of systems through machine learning and deep learning approaches and its implications to the real world Presents data analytics and mining for decision-support applications Offers case-based reasoning

Application of Machine Learning and Deep Learning Methods to Power System Problems

Application of Machine Learning and Deep Learning Methods to Power System Problems
Author: Morteza Nazari-Heris,Somayeh Asadi,Behnam Mohammadi-Ivatloo,Moloud Abdar,Houtan Jebelli,Milad Sadat-Mohammadi
Publsiher: Springer Nature
Total Pages: 391
Release: 2021-11-21
ISBN: 3030776964
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Application of Machine Learning and Deep Learning Methods to Power System Problems Book Excerpt:

This book evaluates the role of innovative machine learning and deep learning methods in dealing with power system issues, concentrating on recent developments and advances that improve planning, operation, and control of power systems. Cutting-edge case studies from around the world consider prediction, classification, clustering, and fault/event detection in power systems, providing effective and promising solutions for many novel challenges faced by power system operators. Written by leading experts, the book will be an ideal resource for researchers and engineers working in the electrical power engineering and power system planning communities, as well as students in advanced graduate-level courses.

Handbook of Research on Emerging Trends and Applications of Machine Learning

Handbook of Research on Emerging Trends and Applications of Machine Learning
Author: Solanki, Arun,Kumar, Sandeep,Nayyar, Anand
Publsiher: IGI Global
Total Pages: 674
Release: 2019-12-13
ISBN: 1522596453
Category: Computers
Language: EN, FR, DE, ES & NL

Handbook of Research on Emerging Trends and Applications of Machine Learning Book Excerpt:

As today’s world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.

Machine Learning Applications

Machine Learning Applications
Author: Rik Das,Siddhartha Bhattacharyya,Sudarshan Nandy
Publsiher: Walter de Gruyter GmbH & Co KG
Total Pages: 153
Release: 2020-04-20
ISBN: 3110608669
Category: Computers
Language: EN, FR, DE, ES & NL

Machine Learning Applications Book Excerpt:

The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have identified huge scope in applying machine learning techniques for gaining meaningful insights. Random growth of unstructured data poses new research challenges to handle this huge source of information. Efficient designing of machine learning techniques is the need of the hour. Recent literature in machine learning has emphasized on single technique of information identification. Huge scope exists in developing hybrid machine learning models with reduced computational complexity for enhanced accuracy of information identification. This book will focus on techniques to reduce feature dimension for designing light weight techniques for real time identification and decision fusion. Key Findings of the book will be the use of machine learning in daily lives and the applications of it to improve livelihood. However, it will not be able to cover the entire domain in machine learning in its limited scope. This book is going to benefit the research scholars, entrepreneurs and interdisciplinary approaches to find new ways of applications in machine learning and thus will have novel research contributions. The lightweight techniques can be well used in real time which will add value to practice.

Deep Learning for Time Series Forecasting

Deep Learning for Time Series Forecasting
Author: Jason Brownlee
Publsiher: Machine Learning Mastery
Total Pages: 572
Release: 2018-08-30
ISBN: 1928374650XXX
Category: Computers
Language: EN, FR, DE, ES & NL

Deep Learning for Time Series Forecasting Book Excerpt:

Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of temporal structures like trends and seasonality. With clear explanations, standard Python libraries, and step-by-step tutorial lessons you’ll discover how to develop deep learning models for your own time series forecasting projects.

Deep Learning Applications in Medical Imaging

Deep Learning Applications in Medical Imaging
Author: Saxena, Sanjay,Paul, Sudip
Publsiher: IGI Global
Total Pages: 274
Release: 2020-10-16
ISBN: 1799850722
Category: Medical
Language: EN, FR, DE, ES & NL

Deep Learning Applications in Medical Imaging 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.