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Demystifying Big Data Machine Learning And Deep Learning For Healthcare Analytics

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Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics

Demystifying Big Data  Machine Learning  and Deep Learning for Healthcare Analytics Book
Author : Pradeep N,Sandeep Kautish,Sheng Lung Peng
Publisher : Elsevier
Release : 2021-06-14
ISBN : 0128216336
Language : En, Es, Fr & De

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Book Description :

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians. Provides a comprehensive reference for biomedical engineers, computer scientists, advanced industry practitioners, researchers, and clinicians to understand and develop healthcare analytics using advanced tools and technologies Includes in-depth illustrations of advanced techniques via dataset samples, statistical tables, and graphs with algorithms and computational methods for developing new applications in healthcare informatics Unique case study approach provides readers with insights for practical clinical implementation

Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics

Demystifying Big Data  Machine Learning  and Deep Learning for Healthcare Analytics Book
Author : Pradeep N,Sandeep Kautish,Sheng-Lung Peng
Publisher : Academic Press
Release : 2021-06-25
ISBN : 0128220449
Language : En, Es, Fr & De

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Book Description :

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians. Provides a comprehensive reference for biomedical engineers, computer scientists, advanced industry practitioners, researchers, and clinicians to understand and develop healthcare analytics using advanced tools and technologies Includes in-depth illustrations of advanced techniques via dataset samples, statistical tables, and graphs with algorithms and computational methods for developing new applications in healthcare informatics Unique case study approach provides readers with insights for practical clinical implementation

Demystifying Big Data and Machine Learning for Healthcare

Demystifying Big Data and Machine Learning for Healthcare Book
Author : Prashant Natarajan,John C. Frenzel,Detlev H. Smaltz
Publisher : CRC Press
Release : 2017-02-15
ISBN : 1315389304
Language : En, Es, Fr & De

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Book Description :

Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.

Demystifying Big Data and Machine Learning for Healthcare

Demystifying Big Data and Machine Learning for Healthcare Book
Author : Prashant Natarajan,John C. Frenzel,Detlev H. Smaltz
Publisher : CRC Press
Release : 2017-02-15
ISBN : 1315389312
Language : En, Es, Fr & De

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Book Description :

Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.

Computational Intelligence in Robotics and Automation

Computational Intelligence in Robotics and Automation Book
Author : S.S Nandhini,M Karthiga,S B Goyal
Publisher : CRC Press
Release : 2022-09-29
ISBN : 1000686515
Language : En, Es, Fr & De

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Book Description :

This book will help readers to understand the concepts of computational intelligence in automation industries, industrial IoT (IIOT), cognitive systems, data science, and Ecommerce real time applications. The book: Covers computational intelligence in automation industries, industrial IoT (IIOT) , cognitive systems and medical Imaging Discusses intelligent robotics applications with the integration of automation and artificial intelligence Covers foundations of the mathematical concepts applied in robotics and industry automation applications Provides application of artificial intelligence (AI) in the area of computational intelligence The text covers important topics including computational intelligence mathematical modeling, cognitive manufacturing in industry 4.0, artificial intelligence algorithms in robot development, collaborative robots and industrial IoT (IIoT), medical imaging, and multi-robot systems. The text will be useful for graduate students, professional and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer science. Discussing the advantages of the integrated platform of industry automation, robotics and computational intelligence, this text will be useful for graduate students, professional and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer science. It enlightens the foundations of the mathematical concepts applied in robotics and industry automation applications.

Digital Health Transformation with Blockchain and Artificial Intelligence

Digital Health Transformation with Blockchain and Artificial Intelligence Book
Author : Chinmay Chakraborty
Publisher : CRC Press
Release : 2022-05-11
ISBN : 1000580946
Language : En, Es, Fr & De

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Book Description :

The book Digital Health Transformation with Blockchain and Artificial Intelligence covers the global digital revolution in the field of healthcare sector. The population has been overcoming the COVID-19 period; therefore, we need to establish intelligent digital healthcare systems using various emerging technologies like Blockchain and Artificial Intelligence. Internet of Medical Things is the technological revolution that has included the element of "smartness" in the healthcare industry and also identifying, monitoring, and informing service providers about the patient’s clinical information with faster delivery of care services. This book highlights the important issues i.e. (a) How Internet of things can be integrated with the healthcare ecosystem for better diagnostics, monitoring, and treatment of the patients, (b) Artificial Intelligence for predictive and preventive healthcare systems, (c) Blockchain for managing healthcare data to provide transparency, security, and distributed storage, and (d) Effective remote diagnostics and telemedicine approach for developing smart care. The book encompasses chapters belong to the blockchain, Artificial Intelligence, and Big health data technologies. Features: Blockchain and internet of things in healthcare systems Secure Digital Health Data Management in Internet of Things Public Perception towards AI-Driven Healthcare Security, privacy issues and challenges in adoption of smart digital healthcare Big data analytics and Internet of things in the pandemic era Clinical challenges for digital health revolution Artificial intelligence for advanced healthcare Future Trajectory of Healthcare with Artificial Intelligence 9 Parkinson disease pre-diagnosis using smart technologies Emerging technologies to combat the COVID-19 Machine Learning and Internet of Things in Digital Health Transformation Effective Remote Healthcare and Telemedicine Approaches Legal implication of blockchain technology in public health This Book on "Digital Health Transformation with Blockchain and Artificial Intelligence" aims at promoting and facilitating exchanges of research knowledge and findings across different disciplines on the design and investigation of secured healthcare data analytics. It can also be used as a textbook for a Masters course in security and biomedical engineering. This book will also present new methods for the medical data analytics, blockchain technology, and diagnosis of different diseases to improve the quality of life in general, and better integration into digital healthcare.

Demystifying AI for the Enterprise

Demystifying AI for the Enterprise Book
Author : Prashant Natarajan,Bob Rogers,Edward Dixon,Jonas Christensen,Kirk Borne,Leland Wilkinson,Shantha Mohan
Publisher : CRC Press
Release : 2021-12-31
ISBN : 1351032925
Language : En, Es, Fr & De

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Book Description :

Artificial intelligence (AI) in its various forms –– machine learning, chatbots, robots, agents, etc. –– is increasingly being seen as a core component of enterprise business workflow and information management systems. The current promise and hype around AI are being driven by software vendors, academic research projects, and startups. However, we posit that the greatest promise and potential for AI lies in the enterprise with its applications touching all organizational facets. With increasing business process and workflow maturity, coupled with recent trends in cloud computing, datafication, IoT, cybersecurity, and advanced analytics, there is an understanding that the challenges of tomorrow cannot be solely addressed by today’s people, processes, and products. There is still considerable mystery, hype, and fear about AI in today’s world. A considerable amount of current discourse focuses on a dystopian future that could adversely affect humanity. Such opinions, with understandable fear of the unknown, don’t consider the history of human innovation, the current state of business and technology, or the primarily augmentative nature of tomorrow’s AI. This book demystifies AI for the enterprise. It takes readers from the basics (definitions, state-of-the-art, etc.) to a multi-industry journey, and concludes with expert advice on everything an organization must do to succeed. Along the way, we debunk myths, provide practical pointers, and include best practices with applicable vignettes. AI brings to enterprise the capabilities that promise new ways by which professionals can address both mundane and interesting challenges more efficiently, effectively, and collaboratively (with humans). The opportunity for tomorrow’s enterprise is to augment existing teams and resources with the power of AI in order to gain competitive advantage, discover new business models, establish or optimize new revenues, and achieve better customer and user satisfaction.

Emerging Technologies in Healthcare

Emerging Technologies in Healthcare Book
Author : Matthew N. O. Sadiku,Rotimi A. K. Jaiyesimi,Joyce B. Idehen,Sarhan M. Musa
Publisher : AuthorHouse
Release : 2021-10-05
ISBN : 1665528427
Language : En, Es, Fr & De

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Book Description :

Health is regarded as one of the global challenges for mankind. Healthcare is a complex system that covers processes of diagnosis, treatment, and prevention of diseases. It constitutes a fundamental pillar of the modern society. Modern healthcare is technological healthcare. Technology is everywhere. This book focuses on twenty-one emerging technologies in the healthcare industry. An emerging technology is one that holds the promise of creating a new economic engine and is trans-industrial. Emerging technological trends are rapidly transforming businesses in general and healthcare in particular in ways that we find hard to imagine. Artificial intelligence (AI), machine learning, robots, blockchain, cloud computing, Internet of things (IoT), and augmented & virtual reality are some of the technologies at the heart of this revolution and are covered in this book. The convergence of these technologies is upon us and will have a huge impact on the patient experience

Intelligent Healthcare

Intelligent Healthcare Book
Author : Chinmay Chakraborty
Publisher : Springer Nature
Release : 2022
ISBN : 9811681503
Language : En, Es, Fr & De

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Book Description :

The book Intelligent Healthcare: Infrastructure, Algorithms, and Management® cover a wide range of research topics on innovative intelligent healthcare solutions and advancements with the latest research developments. Data analytics are relevant for healthcare to meet many technical challenges and issues that need to be addressed to realize this potential. The advanced healthcare systems have to be upgraded with new capabilities such as data analytics, machine learning, intelligent decision making, and more professional services. The Internet of Things helps to design and develop intelligent healthcare solutions assisted by security, data analytics, and machine learning. This book will provide federated learning, Data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart healthcare. This book aims to attract works on multidisciplinary research spanning across computer science and engineering, environmental studies, services, urban planning and development, Healthcare, social sciences, and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative learning and computing solutions and big medical data-powered applications to cope with the real-world challenges for building smart healthcare sectors. Main Features: Ø Immersive technologies in healthcare Ø Internet of medical things Ø Federated learning algorithms Ø Explainable AI in Pervasive Healthcare Ø New management principles using biomedical data Ø Secured healthcare management systems This book aims to set up a better understanding of data scientists, researchers, and technologists under innovative digital health. The reader can find out existing research challenges, current market trends, and low-cost technologies to smoothly address the digital health issue.

Machine Learning with Health Care Perspective

Machine Learning with Health Care Perspective Book
Author : Vishal Jain,Jyotir Moy Chatterjee
Publisher : Springer Nature
Release : 2020-03-09
ISBN : 3030408507
Language : En, Es, Fr & De

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Book Description :

This unique book introduces a variety of techniques designed to represent, enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. Providing a unique compendium of current and emerging machine learning paradigms for healthcare informatics, it reflects the diversity, complexity, and the depth and breadth of this multi-disciplinary area. Further, it describes techniques for applying machine learning within organizations and explains how to evaluate the efficacy, suitability, and efficiency of such applications. Featuring illustrative case studies, including how chronic disease is being redefined through patient-led data learning, the book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare challenges.

Intelligence Based Medicine

Intelligence Based Medicine Book
Author : Anthony C. Chang
Publisher : Academic Press
Release : 2020-06-27
ISBN : 0128233389
Language : En, Es, Fr & De

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Book Description :

Intelligence-Based Medicine: Data Science, Artificial Intelligence, and Human Cognition in Clinical Medicine and Healthcare provides a multidisciplinary and comprehensive survey of artificial intelligence concepts and methodologies with real life applications in healthcare and medicine. Authored by a senior physician-data scientist, the book presents an intellectual and academic interface between the medical and the data science domains that is symmetric and balanced. The content consists of basic concepts of artificial intelligence and its real-life applications in a myriad of medical areas as well as medical and surgical subspecialties. It brings section summaries to emphasize key concepts delineated in each section; mini-topics authored by world-renowned experts in the respective key areas for their personal perspective; and a compendium of practical resources, such as glossary, references, best articles, and top companies. The goal of the book is to inspire clinicians to embrace the artificial intelligence methodologies as well as to educate data scientists about the medical ecosystem, in order to create a transformational paradigm for healthcare and medicine by using this emerging new technology. Covers a wide range of relevant topics from cloud computing, intelligent agents, to deep reinforcement learning and internet of everything Presents the concepts of artificial intelligence and its applications in an easy-to-understand format accessible to clinicians and data scientists Discusses how artificial intelligence can be utilized in a myriad of subspecialties and imagined of the future Delineates the necessary elements for successful implementation of artificial intelligence in medicine and healthcare

Machine Learning for Healthcare

Machine Learning for Healthcare Book
Author : Rashmi Agrawal,Jyotir Moy Chatterjee,Abhishek Kumar,Pramod Singh Rathore,Dac-Nhuong Le
Publisher : CRC Press
Release : 2020-12-08
ISBN : 1000221881
Language : En, Es, Fr & De

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Book Description :

Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data through machine learning methods. This book expresses the long-standing challenges in healthcare informatics and provides rational explanations of how to deal with them. Machine Learning for Healthcare: Handling and Managing Data provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of machine learning applications. These are illustrated in a case study which examines how chronic disease is being redefined through patient-led data learning and the Internet of Things. This text offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare. Readers will discover the ethical implications of machine learning in healthcare and the future of machine learning in population and patient health optimization. This book can also help assist in the creation of a machine learning model, performance evaluation, and the operationalization of its outcomes within organizations. It may appeal to computer science/information technology professionals and researchers working in the area of machine learning, and is especially applicable to the healthcare sector. The features of this book include: A unique and complete focus on applications of machine learning in the healthcare sector. An examination of how data analysis can be done using healthcare data and bioinformatics. An investigation of how healthcare companies can leverage the tapestry of big data to discover new business values. An exploration of the concepts of machine learning, along with recent research developments in healthcare sectors.

Information and Communication Technologies for Development Evaluation

Information and Communication Technologies for Development Evaluation Book
Author : Oscar A. García,Prashanth Kotturi
Publisher : Routledge
Release : 2019-07-09
ISBN : 042965054X
Language : En, Es, Fr & De

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Book Description :

Written by a team of expert practitioners at the Independent Office of Evaluation of International Fund for Agricultural Development (IFAD), this book gives an insight into the implications of new and emerging technologies in development evaluation. Growing technologies such as big data analytics, machine learning and remote sensing present new opportunities for development practitioners and development evaluators, particularly when measuring indicators of the Sustainable Development Goals. The volume provides an overview of information and communication technologies (ICTs) in the context of evaluation, looking at the theory and practice, and discussing how the landscape may unfold. It also considers concerns about privacy, ethics and inclusion, which are crucial issues for development practitioners and evaluators working in the interests of vulnerable populations across the globe. Among the contributions are case studies of seven organizations using various technologies for data collection, analysis, dissemination and learning. This valuable insight into practice will be of interest to researchers, practitioners and policymakers in development economics, development policy and ICT.

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare Book
Author : Adam Bohr,Kaveh Memarzadeh
Publisher : Academic Press
Release : 2020-06-21
ISBN : 0128184396
Language : En, Es, Fr & De

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Book Description :

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Big Data and Artificial Intelligence for Healthcare Applications

Big Data and Artificial Intelligence for Healthcare Applications Book
Author : Ankur Saxena,Nicolas Brault,Shazia Rashid
Publisher : CRC Press
Release : 2021-06-15
ISBN : 1000387313
Language : En, Es, Fr & De

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Book Description :

This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it. This book explores the applications in different areas of healthcare and highlights the current research. "Big Data and Artificial Intelligence for Healthcare Applications" covers healthcare big data analytics, mobile health and personalized medicine, clinical trial data management and presents how Artificial Intelligence can be used for early disease diagnosis prediction and prognosis. It also offers some case studies that describes the application of Artificial Intelligence and Machine Learning in healthcare. Researchers, healthcare professionals, data scientists, systems engineers, students, programmers, clinicians, and policymakers will find this book of interest.

A Global Approach to Data Value Maximization

A Global Approach to Data Value Maximization Book
Author : Paolo Dell’Aversana
Publisher : Cambridge Scholars Publishing
Release : 2019-04-17
ISBN : 1527533379
Language : En, Es, Fr & De

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Book Description :

This book presents a systematic discussion about methods and techniques used to extract the maximum informative value from complex data sets. A multitude of approaches and techniques can be applied for that purpose, including data fusion and model integration, multimodal data analysis in different physical domains, audio-video display of data through techniques of “sonification”, multimedia machine learning, and hybrid methods of data analysis. The book begins with the domain of geosciences, before moving on to other scientific areas, like diagnostic medicine and various engineering sectors. As such, it will appeal to a large audience, including geologists and geophysicists, data scientists, physicians and cognitive scientists, and experts in social sciences and knowledge management.

Demystifying Federated Learning for Blockchain and Industrial Internet of Things

Demystifying Federated Learning for Blockchain and Industrial Internet of Things Book
Author : Kautish, Sandeep,Dhiman, Gaurav
Publisher : IGI Global
Release : 2022-06-17
ISBN : 166843735X
Language : En, Es, Fr & De

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Book Description :

In recent years, mobile technology and the internet of objects have been used in mobile networks to meet new technical demands. Emerging needs have centered on data storage, computation, and low latency management in potentially smart cities, transport, smart grids, and a wide number of sustainable environments. Federated learning’s contributions include an effective framework to improve network security in heterogeneous industrial internet of things (IIoT) environments. Demystifying Federated Learning for Blockchain and Industrial Internet of Things rediscovers, redefines, and reestablishes the most recent applications of federated learning using blockchain and IIoT to optimize data for next-generation networks. It provides insights to readers in a way of inculcating the theme that shapes the next generation of secure communication. Covering topics such as smart agriculture, object identification, and educational big data, this premier reference source is an essential resource for computer scientists, programmers, government officials, business leaders and managers, students and faculty of higher education, researchers, and academicians.

Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics

Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics Book
Author : Abhishek Kumar,Anavatti G. Sreenatha,Ashutosh Kumar Dubey,Pramod Singh Rathore
Publisher : CRC Press
Release : 2022
ISBN : 9781003132110
Language : En, Es, Fr & De

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Book Description :

"In the last two decades, machine learning has been dramatically developed and is still experiencing a fast and ever-lasting change in paradigm, methodology, applications, and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on the diversity and complexity. Machine Learning Approaches and Applications Applied Intelligence for Healthcare Data Analytics presents a variety of techniques design to enhance and empower multi-disciplinary and multi-institutional machine learning research. It provides many case studies and a panoramic view of data and machine learning techniques providing the opportunity for novel insights and discoveries. The book explores the theory and practical applications in healthcare and includes a guided tour of machine learning algorithms, architecture design, along with interdisciplinary challenges. This book is useful to research scholars and students involved in critical condition analysis and computation models"--

Handbook of Research on Emerging Trends and Applications of Machine Learning

Handbook of Research on Emerging Trends and Applications of Machine Learning Book
Author : Solanki, Arun,Kumar, Sandeep,Nayyar, Anand
Publisher : IGI Global
Release : 2019-12-13
ISBN : 1522596453
Language : En, Es, Fr & De

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Book Description :

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.

Advances in Surgery 2020

Advances in Surgery 2020 Book
Author : John L. Cameron
Publisher : Elsevier Health Sciences
Release : 2020-08-30
ISBN : 0323755240
Language : En, Es, Fr & De

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Book Description :

Each year, Advances in Surgery reviews the most current practices in general surgery. A distinguished editorial board, headed by Dr. John Cameron, identifies key areas of major progress and controversy and invites preeminent specialists to contribute original articles devoted to these topics. These insightful overviews in general surgery bring concepts to a clinical level and explore their everyday impact on patient care.