Applied Computing in Medicine and Health
Applied Computing in Medicine and Health

Author: Dhiya Al-Jumeily

Publisher: Morgan Kaufmann

Published: 2015-08-21

Total Pages: 367

ISBN-13: 012803498X

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Applied Computing in Medicine and Health is a comprehensive presentation of on-going investigations into current applied computing challenges and advances, with a focus on a particular class of applications, primarily artificial intelligence methods and techniques in medicine and health. Applied computing is the use of practical computer science knowledge to enable use of the latest technology and techniques in a variety of different fields ranging from business to scientific research. One of the most important and relevant areas in applied computing is the use of artificial intelligence (AI) in health and medicine. Artificial intelligence in health and medicine (AIHM) is assuming the challenge of creating and distributing tools that can support medical doctors and specialists in new endeavors. The material included covers a wide variety of interdisciplinary perspectives concerning the theory and practice of applied computing in medicine, human biology, and health care. Particular attention is given to AI-based clinical decision-making, medical knowledge engineering, knowledge-based systems in medical education and research, intelligent medical information systems, intelligent databases, intelligent devices and instruments, medical AI tools, reasoning and metareasoning in medicine, and methodological, philosophical, ethical, and intelligent medical data analysis. - Discusses applications of artificial intelligence in medical data analysis and classifications - Provides an overview of mobile health and telemedicine with specific examples and case studies - Explains how behavioral intervention technologies use smart phones to support a patient centered approach - Covers the design and implementation of medical decision support systems in clinical practice using an applied case study approach

Cloud Computing Systems and Applications in Healthcare
Cloud Computing Systems and Applications in Healthcare

Author: Bhatt, Chintan M.

Publisher: IGI Global

Published: 2016-08-30

Total Pages: 303

ISBN-13: 1522510036

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The implementation of cloud technologies in healthcare is paving the way to more effective patient care and management for medical professionals around the world. As more facilities start to integrate cloud computing into their healthcare systems, it is imperative to examine the emergent trends and innovations in the field. Cloud Computing Systems and Applications in Healthcare features innovative research on the impact that cloud technology has on patient care, disease management, and the efficiency of various medical systems. Highlighting the challenges and difficulties in implementing cloud technology into the healthcare field, this publication is a critical reference source for academicians, technology designers, engineers, professionals, analysts, and graduate students.

Artificial Intelligence in Healthcare
Artificial Intelligence in Healthcare

Author: Adam Bohr

Publisher: Academic Press

Published: 2020-06-21

Total Pages: 385

ISBN-13: 0128184396

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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

Artificial Intelligence in Medicine
Artificial Intelligence in Medicine

Author: David Riaño

Publisher: Springer

Published: 2019-06-19

Total Pages: 431

ISBN-13: 303021642X

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This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.

Healthcare Industry 4.0
Healthcare Industry 4.0

Author: P. Karthikeyan

Publisher: CRC Press

Published: 2023-08-28

Total Pages: 213

ISBN-13: 1000930637

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This book covers computer vision-based applications in digital healthcare industry 4.0, including different computer vision techniques, image classification, image segmentations, and object detection. Various application case studies from domains such as science, engineering, and social networking are introduced, along with their architecture and how they leverage various technologies, such as edge computing and cloud computing. It also covers applications of computer vision in tumor detection, cancer detection, combating COVID-19, and patient monitoring. Features: Provides a state-of-the-art computer vision application in the digital health care industry Reviews advances in computer vision and data science technologies for analyzing information on human function and disability Includes practical implementation of computer vision application using recent tools and software Explores computer vision-enabled medical/clinical data security in the cloud Includes case studies from the leading computer vision integrated vendors like Amazon, Microsoft, IBM, and Google This book is aimed at researchers and graduate students in bioengineering, intelligent systems, and computer science and engineering.

Applied Computer Sciences in Engineering
Applied Computer Sciences in Engineering

Author: Juan Carlos Figueroa-García

Publisher: Springer Nature

Published: 2021-09-29

Total Pages: 534

ISBN-13: 3030867021

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This volume constitutes the refereed proceedings of the 8th Workshop on Engineering Applications, WEA 2021, held in Medellín, Colombia, in October 2021. Due to the COVID-19 pandemic the conference was held in a hybrid mode. The 33 revised full papers and 11 short papers presented in this volume were carefully reviewed and selected from 127 submissions. The papers are organized in the following topical sections: computational intelligence; bioengineering; Internet of Things (IoT); optimization and operations research; engineering applications.

Next-Generation Mobile and Pervasive Healthcare Solutions
Next-Generation Mobile and Pervasive Healthcare Solutions

Author: Machado, Jose

Publisher: IGI Global

Published: 2017-08-10

Total Pages: 305

ISBN-13: 1522528520

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Technology is changing the practice of healthcare by the ways medical information is stored, shared, and accessed. With mobile innovations, new strategies are unfolding to further advance processes and procedures in medical settings. Next-Generation Mobile and Pervasive Healthcare Solutions is an advanced reference source for the latest research on emerging progress and applications within mobile health initiatives and health informatics. Featuring coverage on a broad range of topics and perspectives such as electronic health records (EHR), clinical decision support systems, and medical ontologies, this publication is ideally designed for professionals and researchers seeking scholarly material on the increased use of mobile health applications.

Advances in Artificial Intelligence and Machine Learning Applications for the Imaging of Bone and Soft Tissue Tumors
Advances in Artificial Intelligence and Machine Learning Applications for the Imaging of Bone and Soft Tissue Tumors

Author: Brandon K. K. Fields

Publisher: Frontiers Media SA

Published: 2024-11-07

Total Pages: 119

ISBN-13: 2832556418

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Increasing interest in the development and validation of quantitative imaging biomarkers for oncologic imaging has in recent years inspired a surge in the field of artificial intelligence and machine learning. Initial results showed promise in identifying potential markers of treatment response, malignant potential, and prognostic predictors, among others; however, while many of these early algorithms showed the optimistic ability to separate pathologic states on “in-house” datasets, it was often the case that these classifiers generalized poorly on external validation sets and thus were of limited utility in the clinical setting. This issue was additionally compounded by the frequent use of data filtering and feature selection techniques in many studies to further bolster the machine learning results in limited case scenarios, thereby biasing the overall fit and further reducing generalizability.

Big Data Analytics and Intelligence
Big Data Analytics and Intelligence

Author: Poonam Tanwar

Publisher: Emerald Group Publishing

Published: 2020-09-30

Total Pages: 392

ISBN-13: 1839090995

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Big Data Analytics and Intelligence is essential reading for researchers and experts working in the fields of health care, data science, analytics, the internet of things, and information retrieval.

Applied Computer Vision and Soft Computing with Interpretable AI
Applied Computer Vision and Soft Computing with Interpretable AI

Author: Swati V. Shinde

Publisher: CRC Press

Published: 2023-10-05

Total Pages: 333

ISBN-13: 1000952495

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This reference text presents the knowledge base of computer vision and soft computing techniques with their applications for sustainable developments. Features: Covers a variety of deep learning architectures useful for computer vision tasks Demonstrates the use of different soft computing techniques and their applications for different computer vision tasks Highlights the unified strengths of hybrid techniques based on deep learning and soft computing taken together that give the interpretable, adaptive, and optimized solution to a given problem Addresses the different issues and further research opportunities in computer vision and soft computing Describes all the concepts with practical examples and case studies with appropriate performance measures that validate the applicability of the respective technique to a certain domain Considers recent real word problems and the prospective solutions to these problems This book will be useful to researchers, students, faculty, and industry personnel who are eager to explore the power of deep learning and soft computing for different computer vision tasks.