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Machine Learning In Healthcare And Security


Machine Learning In Healthcare And Security
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Machine Learning In Healthcare And Security


Machine Learning In Healthcare And Security
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Author : Prashant Pranav
language : en
Publisher: CRC Press
Release Date : 2024-01-19

Machine Learning In Healthcare And Security written by Prashant Pranav and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-19 with Computers categories.


This book brings together a blend of different areas of machine learning and recent advances in the area. From the use of ML in healthcare to security, this book encompasses several areas related to ML while keeping a check on traditional ML algorithms. Machine Learning in Healthcare and Security: Advances, Obstacles, and Solutions describes the predictive analysis and forecasting techniques in different emerging and classical areas using the approaches of ML and AI. It discusses the application of ML and AI in medical diagnostic systems and deals with the security prevention aspects of ML and how it can be used to tackle various emerging security issues. This book also focuses on NLP and understanding the techniques, obstacles, and possible solutions. This is a valuable reference resource for researchers and postgraduate students in healthcare systems engineering, computer science, cyber-security, information technology, and applied mathematics.



Smart Healthcare Systems


Smart Healthcare Systems
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Author : Adwitiya Sinha
language : en
Publisher: Chapman & Hall/CRC
Release Date : 2019

Smart Healthcare Systems written by Adwitiya Sinha and has been published by Chapman & Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Artificial intelligence categories.


About the Book The book provides details of applying intelligent mining techniques for extracting & pre-processing medical data from various sources, for application-based healthcare research. Moreover, different datasets are used, thereby exploring real-world case studies related to medical informatics. This book would provide insight to the learners about Machine Learning, Data Analytics, and Sustainable Computing. Salient Features of the Book Exhaustive coverage of Data Analysis using R Real-life healthcare models for: Visually Impaired Disease Diagnosis & Treatment options Applications of Big Data & Deep Learning in Healthcare Drug Discovery Complete guide to learn the knowledge discovery process, build versatile real life healthcare applications Compare & analyze recent healthcare technologies and trends Target Audience This book is mainly targeted at researchers, undergraduate, postgraduate students, academicians, and scholars working in the area of data science and its application to health sciences. Also, the book is beneficial for engineers who are engaged in developing actual healthcare solutions. ng in Healthcare Drug Discovery Complete guide to learn the knowledge discovery process, build versatile real life healthcare applications Compare & analyze recent healthcare technologies and trends Target Audience This book is mainly targeted at researchers, undergraduate, postgraduate students, academicians, and scholars working in the area of data science and its application to health sciences. Also, the book is beneficial for engineers who are engaged in developing actual healthcare solutions.



Machine Learning In Healthcare


Machine Learning In Healthcare
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Author : Bikesh Kumar Singh
language : en
Publisher: CRC Press
Release Date : 2022-02-17

Machine Learning In Healthcare written by Bikesh Kumar Singh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-17 with Computers categories.


Artificial intelligence (AI) and machine learning (ML) techniques play an important role in our daily lives by enhancing predictions and decision-making for the public in several fields such as financial services, real estate business, consumer goods, social media, etc. Despite several studies that have proved the efficacy of AI/ML tools in providing improved healthcare solutions, it has not gained the trust of health-care practitioners and medical scientists. This is due to poor reporting of the technology, variability in medical data, small datasets, and lack of standard guidelines for application of AI. Therefore, the development of new AI/ML tools for various domains of medicine is an ongoing field of research. Machine Learning in Healthcare: Fundamentals and Recent Applications discusses how to build various ML algorithms and how they can be applied to improve healthcare systems. Healthcare applications of AI are innumerable: medical data analysis, early detection and diagnosis of disease, providing objective-based evidence to reduce human errors, curtailing inter- and intra-observer errors, risk identification and interventions for healthcare management, real-time health monitoring, assisting clinicians and patients for selecting appropriate medications, and evaluating drug responses. Extensive demonstrations and discussion on the various principles of machine learning and its application in healthcare is provided, along with solved examples and exercises. This text is ideal for readers interested in machine learning without any background knowledge and looking to implement machine-learning models for healthcare systems.



Artificial Intelligence In Healthcare


Artificial Intelligence In Healthcare
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Author : Adam Bohr
language : en
Publisher: Academic Press
Release Date : 2020-06-21

Artificial Intelligence In Healthcare written by Adam Bohr and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-21 with Computers categories.


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



Machine Learning And The Internet Of Medical Things In Healthcare


Machine Learning And The Internet Of Medical Things In Healthcare
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Author : Krishna Kant Singh
language : en
Publisher: Academic Press
Release Date : 2021-04-14

Machine Learning And The Internet Of Medical Things In Healthcare written by Krishna Kant Singh and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-14 with Science categories.


Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. It also presents the concepts of the Internet of Things, the set of technologies that develops traditional devices into smart devices. Finally, the book offers research perspectives, covering the convergence of machine learning and IoT. It also presents the application of these technologies in the development of healthcare frameworks. - Provides an introduction to the Internet of Medical Things through the principles and applications of machine learning - Explains the functions and applications of machine learning in various applications such as ultrasound imaging, biomedical signal processing, robotics, and biomechatronics - Includes coverage of the evolution of healthcare applications with machine learning, including Clinical Decision Support Systems, artificial intelligence in biomedical engineering, and AI-enabled connected health informatics, supported by real-world case studies



Machine Learning For Health Informatics


Machine Learning For Health Informatics
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Author : Andreas Holzinger
language : en
Publisher: Springer
Release Date : 2016-12-09

Machine Learning For Health Informatics written by Andreas Holzinger and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-09 with Computers categories.


Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds, it is aimed to support human intelligence with machine intelligence. This state-of-the-art survey is an output of the international HCI-KDD expert network and features 22 carefully selected and peer-reviewed chapters on hot topics in machine learning for health informatics; they discuss open problems and future challenges in order to stimulate further research and international progress in this field.



Introduction To Machine Learning In The Cloud With Python


Introduction To Machine Learning In The Cloud With Python
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Author : Pramod Gupta
language : en
Publisher: Springer Nature
Release Date : 2021-04-28

Introduction To Machine Learning In The Cloud With Python written by Pramod Gupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-28 with Technology & Engineering categories.


This book provides an introduction to machine learning and cloud computing, both from a conceptual level, along with their usage with underlying infrastructure. The authors emphasize fundamentals and best practices for using AI and ML in a dynamic infrastructure with cloud computing and high security, preparing readers to select and make use of appropriate techniques. Important topics are demonstrated using real applications and case studies.



Blockchain And Machine Learning For E Healthcare Systems


Blockchain And Machine Learning For E Healthcare Systems
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Author : Balusamy Balamurugan
language : en
Publisher: Institution of Engineering and Technology
Release Date : 2020-11-13

Blockchain And Machine Learning For E Healthcare Systems written by Balusamy Balamurugan and has been published by Institution of Engineering and Technology this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-13 with Computers categories.


Blockchain and machine learning technologies can mitigate healthcare issues such as slow access to medical data, poor system interoperability, lack of patient agency, and data quality and quantity for medical research. Blockchain technology facilitates and secures the storage of information in such a way that doctors can see a patient's entire medical history, but researchers see only statistical data instead of any personal information. Machine learning can make use of this data to notice patterns and give accurate predictions, providing more support for the patients and also in research related fields where there is a need for accurate data to predict credible results.



Machine Learning And Deep Learning In Efficacy Improvement Of Healthcare Systems


Machine Learning And Deep Learning In Efficacy Improvement Of Healthcare Systems
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Author : Om Prakash Jena
language : en
Publisher: CRC Press
Release Date : 2021-12

Machine Learning And Deep Learning In Efficacy Improvement Of Healthcare Systems written by Om Prakash Jena and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12 with Medical categories.


"This book describes the fundamental concepts of machine learning and deep learning techniques in a healthcare system. The aim of this book is to describe how deep learning methods are used to insure high quality data processing, medical image and signal analysis, and improved healthcare application"--



Research Anthology On Privatizing And Securing Data


Research Anthology On Privatizing And Securing Data
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2021-04-23

Research Anthology On Privatizing And Securing Data written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-23 with Computers categories.


With the immense amount of data that is now available online, security concerns have been an issue from the start, and have grown as new technologies are increasingly integrated in data collection, storage, and transmission. Online cyber threats, cyber terrorism, hacking, and other cybercrimes have begun to take advantage of this information that can be easily accessed if not properly handled. New privacy and security measures have been developed to address this cause for concern and have become an essential area of research within the past few years and into the foreseeable future. The ways in which data is secured and privatized should be discussed in terms of the technologies being used, the methods and models for security that have been developed, and the ways in which risks can be detected, analyzed, and mitigated. The Research Anthology on Privatizing and Securing Data reveals the latest tools and technologies for privatizing and securing data across different technologies and industries. It takes a deeper dive into both risk detection and mitigation, including an analysis of cybercrimes and cyber threats, along with a sharper focus on the technologies and methods being actively implemented and utilized to secure data online. Highlighted topics include information governance and privacy, cybersecurity, data protection, challenges in big data, security threats, and more. This book is essential for data analysts, cybersecurity professionals, data scientists, security analysts, IT specialists, practitioners, researchers, academicians, and students interested in the latest trends and technologies for privatizing and securing data.