Implementation Strategies for Improving Diversity in Organizations PDF Download
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Author: Hughes, Claretha
Publisher: IGI Global
ISBN: 1799847462
Category : Business & Economics
Languages : en
Pages : 451
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Book Description
Awareness and inclusion are not enough to create effective change in organizations and society. Instead, organizations must implement strategies to ensure that they not only improve diversity, but also place their employees on career development plans that provide the best fit between individual and organizational needs as well as personal characteristics and career roles. Implementation Strategies for Improving Diversity in Organizations is a pivotal reference source that provides crucial research on the application of stratagems designed to increase organizational change, chiefly to integrate diverse individuals, including physically disabled individuals, women, and people of color, into the workforce. The book also looks at discriminatory practices involving the physical appearance of workers. While highlighting topics such as career development, lookism, and ethnic discrimination, this publication explores new, innovative ideas influencing the paradigm shift for the modern workforce as well as the methods of career development. This book is ideally designed for managers, executives, human resources professionals, researchers, business practitioners, academicians, and students.
Author: Hughes, Claretha
Publisher: IGI Global
ISBN: 1799847462
Category : Business & Economics
Languages : en
Pages : 451
Get Book Here
Book Description
Awareness and inclusion are not enough to create effective change in organizations and society. Instead, organizations must implement strategies to ensure that they not only improve diversity, but also place their employees on career development plans that provide the best fit between individual and organizational needs as well as personal characteristics and career roles. Implementation Strategies for Improving Diversity in Organizations is a pivotal reference source that provides crucial research on the application of stratagems designed to increase organizational change, chiefly to integrate diverse individuals, including physically disabled individuals, women, and people of color, into the workforce. The book also looks at discriminatory practices involving the physical appearance of workers. While highlighting topics such as career development, lookism, and ethnic discrimination, this publication explores new, innovative ideas influencing the paradigm shift for the modern workforce as well as the methods of career development. This book is ideally designed for managers, executives, human resources professionals, researchers, business practitioners, academicians, and students.
Author: Thakare, Anuradha Dheeraj
Publisher: IGI Global
ISBN: 1799877108
Category : Medical
Languages : en
Pages : 470
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Book Description
Currently, informatics within the field of public health is a developing and growing industry. Clinical informatics are used in direct patient care by supplying medical practitioners with information that can be used to develop a care plan. Intelligent applications in clinical informatics facilitates with the technology-based solutions to analyze data or medical images and help clinicians to retrieve that information. Decision models aid with making complex decisions especially in uncertain situations. The Handbook of Research on Applied Intelligence for Health and Clinical Informatics is a comprehensive reference book that focuses on the study of resources and methods for the management of healthcare infrastructure and information. This book provides insights on how applied intelligence with deep learning, experiential learning, and more will impact healthcare and clinical information processing. The content explores the representation, processing, and communication of clinical information in natural and engineered systems. This book covers a range of topics including applied intelligence, medical imaging, telehealth, and decision support systems, and also looks at technologies and tools used in the detection and diagnosis of medical conditions such as cancers, diabetes, heart disease, lung disease, and prenatal syndromes. It is an essential reference source for diagnosticians, medical professionals, imaging specialists, data specialists, IT consultants, medical technologists, academicians, researchers, industrial experts, scientists, and students.
Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385
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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
Author: Eric Topol
Publisher: Basic Books
ISBN: 1541644646
Category : Health & Fitness
Languages : en
Pages : 388
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Book Description
A Science Friday pick for book of the year, 2019 One of America's top doctors reveals how AI will empower physicians and revolutionize patient care Medicine has become inhuman, to disastrous effect. The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard. Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved.
Author: Kerrie L. Holley
Publisher: "O'Reilly Media, Inc."
ISBN: 1492063126
Category : Business & Economics
Languages : en
Pages : 222
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Book Description
AI is poised to transform every aspect of healthcare, including the way we manage personal health, from customer experience and clinical care to healthcare cost reductions. This practical book is one of the first to describe present and future use cases where AI can help solve pernicious healthcare problems. Kerrie Holley and Siupo Becker provide guidance to help informatics and healthcare leadership create AI strategy and implementation plans for healthcare. With this book, business stakeholders and practitioners will be able to build knowledge, a roadmap, and the confidence to support AIin their organizations—without getting into the weeds of algorithms or open source frameworks. Cowritten by an AI technologist and a medical doctor who leverages AI to solve healthcare’s most difficult challenges, this book covers: The myths and realities of AI, now and in the future Human-centered AI: what it is and how to make it possible Using various AI technologies to go beyond precision medicine How to deliver patient care using the IoT and ambient computing with AI How AI can help reduce waste in healthcare AI strategy and how to identify high-priority AI application
Author: Andrzej Grzybowski
Publisher: Springer Nature
ISBN: 3030786013
Category : Medical
Languages : en
Pages : 280
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Book Description
This book provides a wide-ranging overview of artificial intelligence (AI), machine learning (ML) and deep learning (DL) algorithms in ophthalmology. Expertly written chapters examine AI in age-related macular degeneration, glaucoma, retinopathy of prematurity and diabetic retinopathy screening. AI perspectives, systems and limitations are all carefully assessed throughout the book as well as the technical aspects of DL systems for retinal diseases including the application of Google DeepMind, the Singapore algorithm, and the Johns Hopkins algorithm. Artificial Intelligence in Ophthalmology meets the need for a resource that reviews the benefits and pitfalls of AI, ML and DL in ophthalmology. Ophthalmologists, optometrists, eye-care workers, neurologists, cardiologists, internal medicine specialists, AI engineers and IT specialists with an interest in how AI can help with early diagnosis and monitoring treatment in ophthalmic patients will find this book to be an indispensable guide to an evolving area of healthcare technology.
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1799881075
Category : Medical
Languages : en
Pages : 689
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Book Description
Telemedicine, which involves electronic communications and software, provides the same clinical services to patients without the requirement of an in-person visit. Essentially, this is considered remote healthcare. Though telemedicine is not a new practice, it has become an increasingly popular form of healthcare delivery due to current events, including the COVID-19 pandemic. Not only are visits being moved onto virtual platforms, but additional materials and correspondence can remain in the digital sphere. Virtual lab results, digital imaging, medical diagnosis, and video consultations are just a few examples that encompass how telemedicine can be used for increased accessibility in healthcare delivery. With telemedicine being used in both the diagnosis and treatment of patients, technology in healthcare can be implemented at almost any phase of the patient experience. As healthcare delivery follows the digital shift, it is important to understand the technologies, benefits and challenges, and overall impacts of the remote healthcare experience. The Research Anthology on Telemedicine Efficacy, Adoption, and Impact on Healthcare Delivery presents the latest research on best practices for adopting telehealth into medical practices and its efficacy and solutions for the improvement of telemedicine, as well as addresses emerging challenges and opportunities, including issues such as securing patient data and providing healthcare accessibility to rural populations. Covering important themes that include doctor-patient relationships, tele-wound monitoring, and telemedicine regulations, this book is essential for healthcare professionals, doctors, medical students, academic and medical libraries, medical technologists, practitioners, stakeholders, researchers, academicians, and students interested in the emerging technological developments and solutions within the field of telemedicine.
Author: Krishna Kant Singh
Publisher: Academic Press
ISBN: 012823217X
Category : Science
Languages : en
Pages : 290
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Book Description
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
Author: Zhengbing Hu
Publisher: Springer
ISBN: 9783030671327
Category : Computers
Languages : en
Pages : 410
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Book Description
This book covers the latest advances for the development of artificial intelligence systems and their applications in various fields from medicine and technology to education. The proceedings comprise refereed papers presented at the Fourth International Conference of Artificial Intelligence, Medical Engineering, Education (AIMEE2020), held at the Mechanical Engineering Institute of the Russian Academy of Sciences, Moscow, Russia, in 3–4 October 2020. Given the rapid development of artificial intelligence systems, the book emphasizes the need for the intensification of training of a growing number of relevant specialists, in particular, in medical engineering to increase the effectiveness of medical diagnosing and treatment. In digital artificial intelligence systems, scientists endeavor to reproduce the innate intellectual abilities of human and other organisms, and the in-depth study of genetic systems and inherited biological processes can provide new approaches to create more and more effective artificial intelligence methods. Topics of the included papers concern thematic materials in the following spheres: mathematics and biomathematics; medical approaches; technological and educational approaches. The book is a compilation of state-of-the-art papers in the field, covering a comprehensive range of subjects that is relevant to business managers and engineering professionals alike. The breadth and depth of these proceedings make them an excellent resource for asset management practitioners, researchers, and academics, as well as undergraduate and postgraduate students interested in artificial intelligence and bioinformatics systems as well as their growing applications. Intended readership includes specialists, students, and other circles of readers who would like to know where artificial intelligence systems can be applied in the future with great benefit.
Author: Sachi Nandan Mohanty
Publisher: John Wiley & Sons
ISBN: 1119791812
Category : Computers
Languages : en
Pages : 418
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Book Description
When considering the idea of using machine learning in healthcare, it is a Herculean task to present the entire gamut of information in the field of intelligent systems. It is, therefore the objective of this book to keep the presentation narrow and intensive. This approach is distinct from others in that it presents detailed computer simulations for all models presented with explanations of the program code. It includes unique and distinctive chapters on disease diagnosis, telemedicine, medical imaging, smart health monitoring, social media healthcare, and machine learning for COVID-19. These chapters help develop a clear understanding of the working of an algorithm while strengthening logical thinking. In this environment, answering a single question may require accessing several data sources and calling on sophisticated analysis tools. While data integration is a dynamic research area in the database community, the specific needs of research have led to the development of numerous middleware systems that provide seamless data access in a result-driven environment. Since this book is intended to be useful to a wide audience, students, researchers and scientists from both academia and industry may all benefit from this material. It contains a comprehensive description of issues for healthcare data management and an overview of existing systems, making it appropriate for introductory and instructional purposes. Prerequisites are minimal; the readers are expected to have basic knowledge of machine learning. This book is divided into 22 real-time innovative chapters which provide a variety of application examples in different domains. These chapters illustrate why traditional approaches often fail to meet customers’ needs. The presented approaches provide a comprehensive overview of current technology. Each of these chapters, which are written by the main inventors of the presented systems, specifies requirements and provides a description of both the chosen approach and its implementation. Because of the self-contained nature of these chapters, they may be read in any order. Each of the chapters use various technical terms which involve expertise in machine learning and computer science.
