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Artificial Intelligence and Machine Learning in Public Healthcare
This book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public health. It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues. Public health requires special attention as it drives economy and education system. COVID-19 is an example—a truly infectious disease outbreak. The vision of WHO is to create public health services that can deal with abovem...
Active Learning to Minimize the Possible Risk of Future Epidemics
Future epidemics are inevitable, and it takes months and even years to collect fully annotated data. The sheer magnitude of data required for machine learning algorithms, spanning both shallow and deep structures, raises a fundamental question: how big data is big enough to effectively tackle future epidemics? In this context, active learning, often referred to as human or expert-in-the-loop learning, becomes imperative, enabling machines to commence learning from day one with minimal labeled data. In unsupervised learning, the focus shifts toward constructing advanced machine learning models like deep structured networks that autonomously learn over time, with human or expert intervention o...
Recent Trends in Image Processing and Pattern Recognition
This three-book set constitutes the refereed proceedings of the Second International Conference on Recent Trends in Image Processing and Pattern Recognition (RTIP2R) 2018, held in Solapur, India, in December 2018. The 173 revised full papers presented were carefully reviewed and selected from 374 submissions. The papers are organized in topical sections in the tree volumes. Part I: computer vision and pattern recognition; machine learning and applications; and image processing. Part II: healthcare and medical imaging; biometrics and applications. Part III: document image analysis; image analysis in agriculture; and data mining, information retrieval and applications.
Intelligent Systems and Methods to Combat Covid-19
This book discusses intelligent systems and methods to prevent further spread of COVID-19, including artificial intelligence, machine learning, computer vision, signal processing, pattern recognition, and robotics. It not only explores detection/screening of COVID-19 positive cases using one type of data, such as radiological imaging data, but also examines how data analytics-based tools can help predict/project future pandemics. In addition, it highlights various challenges and opportunities, like social distancing, and addresses issues such as data collection, privacy, and security, which affect the robustness of AI-driven tools. Also investigating data-analytics-based tools for projections using time series data, pattern analysis tools for unusual pattern discovery (anomaly detection) in image data, as well as AI-enabled robotics and its possible uses, the book will appeal to a broad readership, including academics, researchers and industry professionals.
Document Image Processing
This book is a printed edition of the Special Issue "Document Image Processing" that was published in J. Imaging
Document Processing Using Machine Learning
Document Processing Using Machine Learning aims at presenting a handful of resources for students and researchers working in the document image analysis (DIA) domain using machine learning since it covers multiple document processing problems. Starting with an explanation of how Artificial Intelligence (AI) plays an important role in this domain, the book further discusses how different machine learning algorithms can be applied for classification/recognition and clustering problems regardless the type of input data: images or text. In brief, the book offers comprehensive coverage of the most essential topics, including: · The role of AI for document image analysis · Optical character recognition · Machine learning algorithms for document analysis · Extreme learning machines and their applications · Mathematical foundation for Web text document analysis · Social media data analysis · Modalities for document dataset generation This book serves both undergraduate and graduate scholars in Computer Science/Information Technology/Electrical and Computer Engineering. Further, it is a great fit for early career research scientists and industrialists in the domain.
Medical Imaging
The book discusses varied topics pertaining to advanced or up-to-date techniques in medical imaging using artificial intelligence (AI), image recognition (IR) and machine learning (ML) algorithms/techniques. Further, coverage includes analysis of chest radiographs (chest x-rays) via stacked generalization models, TB type detection using slice separation approach, brain tumor image segmentation via deep learning, mammogram mass separation, epileptic seizures, breast ultrasound images, knee joint x-ray images, bone fracture detection and labeling, and diabetic retinopathy. It also reviews 3D imaging in biomedical applications and pathological medical imaging.
Metaverse Applications for Intelligent Healthcare
Metaverse Applications for Intelligent Healthcare explores the exciting intersection of artificial intelligence (AI) and the metaverse in the field of healthcare. The use of AI technology in healthcare has already shown great potential in assisting with diagnosis, treatment, and patient care. The metaverse, with its immersive virtual environments, has the potential to revolutionize healthcare by making it more accessible, efficient, and personalized. This book introduces various applications of the metaverse in healthcare, including virtual consultations, remote patient monitoring, and virtual rehabilitation. The book discusses how the metaverse can be used to provide immersive experiences t...
Information Technology and Applied Mathematics
This book discusses recent advances and contemporary research in the field of cryptography, security, mathematics and statistics, and their applications in computing and information technology. Mainly focusing on mathematics and applications of mathematics in computer science and information technology, it includes contributions from eminent international scientists, researchers, and scholars. The book helps researchers update their knowledge of cryptography, security, algebra, frame theory, optimizations, stochastic processes, compressive sensing, functional analysis, and complex variables.
Intelligent Computing and Communication
This book features a collection of high-quality, peer-reviewed papers presented at the Third International Conference on Intelligent Computing and Communication (ICICC 2019) held at the School of Engineering, Dayananda Sagar University, Bengaluru, India, on 7 – 8 June 2019. Discussing advanced and multi-disciplinary research regarding the design of smart computing and informatics, it focuses on innovation paradigms in system knowledge, intelligence and sustainability that can be applied to provide practical solutions to a number of problems in society, the environment and industry. Further, the book also addresses the deployment of emerging computational and knowledge transfer approaches, optimizing solutions in various disciplines of science, technology and healthcare.
