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The book discusses how augmented intelligence can increase the efficiency and speed of diagnosis in healthcare organizations. The concept of augmented intelligence can reflect the enhanced capabilities of human decision-making in clinical settings when augmented with computation systems and methods. It includes real-life case studies highlighting impact of augmented intelligence in health care. The book offers a guided tour of computational intelligence algorithms, architecture design, and applications of learning in healthcare challenges. It presents a variety of techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It also presents specific applications of augmented intelligence in health care, and architectural models and frameworks-based augmented solutions.
Book Synopsis Augmented Intelligence in Healthcare: A Pragmatic and Integrated Analysis by : Sushruta Mishra
Download or read book Augmented Intelligence in Healthcare: A Pragmatic and Integrated Analysis written by Sushruta Mishra and published by Springer Nature. This book was released on 2022-04-19 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book discusses how augmented intelligence can increase the efficiency and speed of diagnosis in healthcare organizations. The concept of augmented intelligence can reflect the enhanced capabilities of human decision-making in clinical settings when augmented with computation systems and methods. It includes real-life case studies highlighting impact of augmented intelligence in health care. The book offers a guided tour of computational intelligence algorithms, architecture design, and applications of learning in healthcare challenges. It presents a variety of techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It also presents specific applications of augmented intelligence in health care, and architectural models and frameworks-based augmented solutions.
This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2023), held at London Metropolitan University, London, UK, during June 2023. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students. The book is divided into four volumes.
Book Synopsis Proceedings of Data Analytics and Management by : Abhishek Swaroop
Download or read book Proceedings of Data Analytics and Management written by Abhishek Swaroop and published by Springer Nature. This book was released on 2024-01-29 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2023), held at London Metropolitan University, London, UK, during June 2023. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students. The book is divided into four volumes.
This book constitutes the refereed post-conference proceedings of the 9th International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2023, held in Kristiansand, Norway, during June 28–30, 2023. The 22 full papers and 16 short papers included in this book were carefully reviewed and selected from 87 submissions. They were grouped into various subtopics including Knowledge Exploration in IoT, Medical Informatics, Machine Learning, Text Mining, Natural Language Processing, Cryptocurrency and Blockchain, Application of Artificial Intelligence, and other areas.
Book Synopsis Mining Intelligence and Knowledge Exploration by : Seifedine Kadry
Download or read book Mining Intelligence and Knowledge Exploration written by Seifedine Kadry and published by Springer Nature. This book was released on 2023-09-23 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-conference proceedings of the 9th International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2023, held in Kristiansand, Norway, during June 28–30, 2023. The 22 full papers and 16 short papers included in this book were carefully reviewed and selected from 87 submissions. They were grouped into various subtopics including Knowledge Exploration in IoT, Medical Informatics, Machine Learning, Text Mining, Natural Language Processing, Cryptocurrency and Blockchain, Application of Artificial Intelligence, and other areas.
In the realm of analyzing human emotions through Artificial Intelligence (AI), a myriad of challenges persist. From the intricate nuances of emotional subtleties to the broader concerns of ethical considerations, privacy implications, and the ongoing battle against bias, AI faces a complex landscape when venturing into the understanding of human emotions. These challenges underscore the intricate balance required to navigate the human psyche with accuracy. The book, Using Machine Learning to Detect Emotions and Predict Human Psychology, serves as a guide for innovative solutions in the field of emotion detection through AI. It explores facial expression analysis, where AI decodes real-time emotions through subtle cues such as eyebrow movements and micro-expressions. In speech and voice analysis, the book unveils how AI processes vocal nuances to discern emotions, considering elements like tone, pitch, and language intricacies. Additionally, the power of text analysis is of great importance, revealing how AI extracts emotional tones from diverse textual communications. By weaving these systems together, the book offers a holistic solution to the challenges faced by AI in understanding the complex landscape of human emotions.
Book Synopsis Using Machine Learning to Detect Emotions and Predict Human Psychology by : Rai, Mritunjay
Download or read book Using Machine Learning to Detect Emotions and Predict Human Psychology written by Rai, Mritunjay and published by IGI Global. This book was released on 2024-02-26 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the realm of analyzing human emotions through Artificial Intelligence (AI), a myriad of challenges persist. From the intricate nuances of emotional subtleties to the broader concerns of ethical considerations, privacy implications, and the ongoing battle against bias, AI faces a complex landscape when venturing into the understanding of human emotions. These challenges underscore the intricate balance required to navigate the human psyche with accuracy. The book, Using Machine Learning to Detect Emotions and Predict Human Psychology, serves as a guide for innovative solutions in the field of emotion detection through AI. It explores facial expression analysis, where AI decodes real-time emotions through subtle cues such as eyebrow movements and micro-expressions. In speech and voice analysis, the book unveils how AI processes vocal nuances to discern emotions, considering elements like tone, pitch, and language intricacies. Additionally, the power of text analysis is of great importance, revealing how AI extracts emotional tones from diverse textual communications. By weaving these systems together, the book offers a holistic solution to the challenges faced by AI in understanding the complex landscape of human emotions.
This book covers the relationship of recent technologies (such as Blockchain, IoT, and 5G) with the cloud computing as well as fog computing, and mobile edge computing. The relationship will not be limited to only architecture proposal, trends, and technical advancements. However, the book also explores the possibility of predictive analytics in cloud computing with respect to Blockchain, IoT, and 5G. The recent advancements in the internet-supported distributed computing i.e. cloud computing, has made it possible to process the bulk amount of data in a parallel and distributed. This has made it a lucrative technology to process the data generated from technologies such as Blockchain, IoT, and 5G. However, there are several issues a Cloud Service Provider (CSP) encounters, such as Blockchain security in cloud, IoT elasticity and scalability management in cloud, Service Level Agreement (SLA) compliances for 5G, Resource management, Load balancing, and Fault-tolerance. This edited book will discuss the aforementioned issues in connection with Blockchain, IoT, and 5G. Moreover, the book discusses how the cloud computing is not sufficient and one needs to use fog computing, and edge computing to efficiently process the data generated from IoT, and 5G. Moreover, the book shows how smart city, smart healthcare system, and smart communities are few of the most relevant IoT applications where fog computing plays a significant role. The book discusses the limitation of fog computing and the need for the edge computing to further reduce the network latency to process streaming data from IoT devices. The book also explores power of predictive analytics of Blockchain, IoT, and 5G data in cloud computing with its sister technologies. Since, the amount of resources increases day-by day, artificial intelligence (AI) tools are becoming more popular due to their capability which can be used in solving wide variety of issues, such as minimize the energy consumption of physical servers, optimize the service cost, improve the quality of experience, increase the service availability, efficiently handle the huge data flow, manages the large number of IoT devices, etc.
Book Synopsis Predictive Analytics in Cloud, Fog, and Edge Computing by : Hiren Kumar Thakkar
Download or read book Predictive Analytics in Cloud, Fog, and Edge Computing written by Hiren Kumar Thakkar and published by Springer Nature. This book was released on 2022-12-16 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the relationship of recent technologies (such as Blockchain, IoT, and 5G) with the cloud computing as well as fog computing, and mobile edge computing. The relationship will not be limited to only architecture proposal, trends, and technical advancements. However, the book also explores the possibility of predictive analytics in cloud computing with respect to Blockchain, IoT, and 5G. The recent advancements in the internet-supported distributed computing i.e. cloud computing, has made it possible to process the bulk amount of data in a parallel and distributed. This has made it a lucrative technology to process the data generated from technologies such as Blockchain, IoT, and 5G. However, there are several issues a Cloud Service Provider (CSP) encounters, such as Blockchain security in cloud, IoT elasticity and scalability management in cloud, Service Level Agreement (SLA) compliances for 5G, Resource management, Load balancing, and Fault-tolerance. This edited book will discuss the aforementioned issues in connection with Blockchain, IoT, and 5G. Moreover, the book discusses how the cloud computing is not sufficient and one needs to use fog computing, and edge computing to efficiently process the data generated from IoT, and 5G. Moreover, the book shows how smart city, smart healthcare system, and smart communities are few of the most relevant IoT applications where fog computing plays a significant role. The book discusses the limitation of fog computing and the need for the edge computing to further reduce the network latency to process streaming data from IoT devices. The book also explores power of predictive analytics of Blockchain, IoT, and 5G data in cloud computing with its sister technologies. Since, the amount of resources increases day-by day, artificial intelligence (AI) tools are becoming more popular due to their capability which can be used in solving wide variety of issues, such as minimize the energy consumption of physical servers, optimize the service cost, improve the quality of experience, increase the service availability, efficiently handle the huge data flow, manages the large number of IoT devices, etc.
The Internet of Medical Things (IoMT) is a system that collects data from patients with the help of different sensory inputs, e.g., an accelerometer, electrocardiography, and electroencephalography. This text presents both theoretical and practical concepts related to the application of machine learning and Internet of Things (IoT) algorithms in analyzing data generated through healthcare systems. Illustrates the latest technologies in the healthcare domain and the Internet of Things infrastructure for storing smart electronic health records Focuses on the importance of machine learning algorithms and the significance of Internet of Things infrastructure for healthcare systems Showcases the application of fog computing architecture and edge computing in novel aspects of modern healthcare services Discusses unsupervised genetic algorithm-based automatic heart disease prediction Covers Internet of Things–based hardware mechanisms and machine learning algorithms to predict the stress level of patients The text is primarily written for graduate students and academic researchers in the fields of computer science and engineering, biomedical engineering, electrical engineering, and information technology.
Book Synopsis Internet of Things-Based Machine Learning in Healthcare by : Prasenjit Dey
Download or read book Internet of Things-Based Machine Learning in Healthcare written by Prasenjit Dey and published by CRC Press. This book was released on 2024-06-10 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Internet of Medical Things (IoMT) is a system that collects data from patients with the help of different sensory inputs, e.g., an accelerometer, electrocardiography, and electroencephalography. This text presents both theoretical and practical concepts related to the application of machine learning and Internet of Things (IoT) algorithms in analyzing data generated through healthcare systems. Illustrates the latest technologies in the healthcare domain and the Internet of Things infrastructure for storing smart electronic health records Focuses on the importance of machine learning algorithms and the significance of Internet of Things infrastructure for healthcare systems Showcases the application of fog computing architecture and edge computing in novel aspects of modern healthcare services Discusses unsupervised genetic algorithm-based automatic heart disease prediction Covers Internet of Things–based hardware mechanisms and machine learning algorithms to predict the stress level of patients The text is primarily written for graduate students and academic researchers in the fields of computer science and engineering, biomedical engineering, electrical engineering, and information technology.
This book includes high-quality research papers presented at the Sixth International Conference on Innovative Computing and Communication (ICICC 2023), which is held at the Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India, on February 17–18, 2023. Introducing the innovative works of scientists, professors, research scholars, students, and industrial experts in the field of computing and communication, the book promotes the transformation of fundamental research into institutional and industrialized research and the conversion of applied exploration into real-time applications.
Book Synopsis International Conference on Innovative Computing and Communications by : Aboul Ella Hassanien
Download or read book International Conference on Innovative Computing and Communications written by Aboul Ella Hassanien and published by Springer Nature. This book was released on 2023-07-31 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes high-quality research papers presented at the Sixth International Conference on Innovative Computing and Communication (ICICC 2023), which is held at the Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India, on February 17–18, 2023. Introducing the innovative works of scientists, professors, research scholars, students, and industrial experts in the field of computing and communication, the book promotes the transformation of fundamental research into institutional and industrialized research and the conversion of applied exploration into real-time applications.
This book provides state-of-the-art coverage of deep learning applications in image analysis. The book demonstrates various deep learning algorithms that can offer practical solutions for various image-related problems; also how these algorithms are used by scientists and scholars in industry and academia. This includes autoencoder and deep convolutional generative adversarial network in improving classification performance of Bangla handwritten characters, dealing with deep learning-based approaches using feature selection methods for automatic diagnosis of covid-19 disease from x-ray images, imbalance image data sets of classification, image captioning using deep transfer learning, developing a vehicle over speed detection system, creating an intelligent system for video-based proximity analysis, building a melanoma cancer detection system using deep learning, plant diseases classification using AlexNet, dealing with hyperspectral images using deep learning, chest x-ray image classification of pneumonia disease using efficient net and inceptionv3. The book also addresses the difficulty of implementing deep learning in terms of computation time and the complexity of reasoning and modelling different types of data where information is currently encoded. Each chapter has the application of various new or existing deep learning models such as Deep Neural Network (DNN) and Deep Convolutional Neural Networks (DCNN). The detailed utilization of deep learning packages that are available in MATLAB, Python and R programming environments have also been discussed, therefore, the readers will get to know about the practical implementation of deep learning as well. The content of this book is presented in a simple and lucid style for professionals, nonprofessionals, scientists, and students interested in the research area of deep learning applications in image analysis.
Book Synopsis Deep Learning Applications in Image Analysis by : Sanjiban Sekhar Roy
Download or read book Deep Learning Applications in Image Analysis written by Sanjiban Sekhar Roy and published by Springer Nature. This book was released on 2023-07-08 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides state-of-the-art coverage of deep learning applications in image analysis. The book demonstrates various deep learning algorithms that can offer practical solutions for various image-related problems; also how these algorithms are used by scientists and scholars in industry and academia. This includes autoencoder and deep convolutional generative adversarial network in improving classification performance of Bangla handwritten characters, dealing with deep learning-based approaches using feature selection methods for automatic diagnosis of covid-19 disease from x-ray images, imbalance image data sets of classification, image captioning using deep transfer learning, developing a vehicle over speed detection system, creating an intelligent system for video-based proximity analysis, building a melanoma cancer detection system using deep learning, plant diseases classification using AlexNet, dealing with hyperspectral images using deep learning, chest x-ray image classification of pneumonia disease using efficient net and inceptionv3. The book also addresses the difficulty of implementing deep learning in terms of computation time and the complexity of reasoning and modelling different types of data where information is currently encoded. Each chapter has the application of various new or existing deep learning models such as Deep Neural Network (DNN) and Deep Convolutional Neural Networks (DCNN). The detailed utilization of deep learning packages that are available in MATLAB, Python and R programming environments have also been discussed, therefore, the readers will get to know about the practical implementation of deep learning as well. The content of this book is presented in a simple and lucid style for professionals, nonprofessionals, scientists, and students interested in the research area of deep learning applications in image analysis.
It has become clear that managing and maintaining state-of-the-art healthcare facilities is more important than ever before. Healthcare consists of many different institutions and supports personnel ranging from laboratories of universities, public and private hospitals, research centers of health institutions, public health institutes, institutions, and organizations engaged in research and development in the field of medicine. For all these entities to be successful, there needs to be coordination among the bodies and quality must be kept at a very high level. The Handbook of Research on Quality and Competitiveness in the Healthcare Services Sector considers the current state of the healthcare services sector and examines future directions. Covering topics such as quality excellence models, accreditation, and e-health, this major reference work is an essential resource for economists, healthcare specialists, government officials, consultants, business leaders and executives, healthcare professionals, IT managers, students and educators of higher education, researchers, and academicians.
Book Synopsis Handbook of Research on Quality and Competitiveness in the Healthcare Services Sector by : Akkucuk, Ulas
Download or read book Handbook of Research on Quality and Competitiveness in the Healthcare Services Sector written by Akkucuk, Ulas and published by IGI Global. This book was released on 2023-03-24 with total page 573 pages. Available in PDF, EPUB and Kindle. Book excerpt: It has become clear that managing and maintaining state-of-the-art healthcare facilities is more important than ever before. Healthcare consists of many different institutions and supports personnel ranging from laboratories of universities, public and private hospitals, research centers of health institutions, public health institutes, institutions, and organizations engaged in research and development in the field of medicine. For all these entities to be successful, there needs to be coordination among the bodies and quality must be kept at a very high level. The Handbook of Research on Quality and Competitiveness in the Healthcare Services Sector considers the current state of the healthcare services sector and examines future directions. Covering topics such as quality excellence models, accreditation, and e-health, this major reference work is an essential resource for economists, healthcare specialists, government officials, consultants, business leaders and executives, healthcare professionals, IT managers, students and educators of higher education, researchers, and academicians.
Book Synopsis Current and Future Trends on Intelligent Technology Adoption by : Mohammed A. Al-Sharafi
Download or read book Current and Future Trends on Intelligent Technology Adoption written by Mohammed A. Al-Sharafi and published by Springer Nature. This book was released on with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt:
