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Assessing COVID-19 and Other Pandemics and Epidemics using Computational Modelling and Data Analysis
This book comprehensively covers the topic of COVID-19 and other pandemics and epidemics data analytics using computational modelling. Biomedical and Health Informatics is an emerging field of research at the intersection of information science, computer science, and health care. The new era of pandemics and epidemics bring tremendous opportunities and challenges due to the plentiful and easily available medical data allowing for further analysis. The aim of pandemics and epidemics research is to ensure high-quality, efficient healthcare, better treatment and quality of life by efficiently analyzing the abundant medical, and healthcare data including patient’s data, electronic health recor...
Knowledge Graphs and Semantic Web
This book constitutes the proceedings of the 4th Iberoamerican Conference and third Indo-American Conference on Knowledge Graphs and Semantic Web, KGSWC 2022, which took place in Madrid, Spain, in November 2022. The 22 full and 3 short research papers presented in this volume were carefully reviewed and selected from 63 submissions. The papers cover topics related to software and its engineering, software creation and management, Emerging technologies, Analysis and design of emerging devices and systems, Emerging tools and methodologies and others.
Current Trends in Web Engineering
This volume constitutes the papers of several workshops which were held in conjunction with the ICWE 2022 International Workshops, BECS, SWEET and WALS, held in Bari, Italy, July 5–8, 2022. The 14 revised full papers and 1 short paper presented in this book were carefully reviewed and selected from 25 submissions. ICWE 2022 presents the following three workshops: Second International Workshop on Big Data driven Edge Cloud Services (BECS 2022) First International Workshop on the Semantic WEb of Everything (SWEET 2022) First International Workshop on Web Applications for Life Sciences (WALS 2022)
Issues of Sustainability in AI and New-Age Thematic Investing
In the face of an evolving global landscape characterized by climate change and a pressing need for sustainable development, the finance sector remains at a critical juncture. Traditional financial models struggle to address the challenges posed by the transition to a low-carbon economy, and unlocking private investments for sustainable initiatives remains an uphill battle. The integration of Artificial Intelligence (AI) and Machine Learning (ML) into financial systems presents both promise and peril, with the potential to reshape the industry while posing unprecedented challenges. Issues of Sustainability in AI and New-Age Thematic Investing is a beacon of insight and solutions in the realm of green finance and AI/ML integration. Geared toward academic scholars, policymakers, and industry experts, this book serves as a comprehensive guide to navigating the intricacies of sustainable development and energy transition. By highlighting the pivotal role of AI/ML in green finance, the publication bridges the gap between theoretical understanding and practical implementation, offering actionable solutions for unlocking private investments.
Artificial Intelligence Approaches to Sustainable Accounting
In an age defined by unparalleled technological advancements, globalization, and the looming specter of environmental and societal crises, the need for a holistic and sustainable approach to accounting practices has never been more pressing. Academic scholars stand witness to the challenges posed by the new era, characterized by transformative shifts across industry, education, community, and society at large. These shifts, driven by rapid advancements in Artificial Intelligence (AI), present a double-edged sword. While AI offers unprecedented opportunities for innovation, it also amplifies the urgency of addressing sustainability concerns. Today's society grapples with the immense responsib...
The Future of Indigenous Inclusivity: Unlocking Finance for Economic Development
The future of Indigenous inclusivity in economic development depends on new financial opportunities to empower Indigenous communities to thrive while preserving their cultural heritage. As global economies shift toward sustainability and equity, there is growing recognition of the need to support Indigenous peoples in accessing finance, technology, and resources necessary to create sustainable growth. By creating inclusive financial systems, promoting Indigenous-led entrepreneurship, and investing in community-driven projects, communities and local businesses can bridge the gap between historical inequities and modern economic opportunities. Exploring this approach may benefit Indigenous com...
Machine Learning for Healthcare Systems
The introduction of digital technology in the healthcare industry is marked by ongoing difficulties with implementation and use. Slow progress has been made in unifying different healthcare systems, and much of the world still lacks a fully integrated healthcare system. The intrinsic complexity and development of human biology, as well as the differences across patients, have repeatedly demonstrated the significance of the human element in the diagnosis and treatment of illnesses. But as digital technology develops, healthcare providers will undoubtedly need to use it more and more to give patients the best treatment possible. The extensive use of machine learning in numerous industries, inc...
Next-Generation Sequencing of Human Antibody Repertoires for Exploring B-cell Landscape, Antibody Discovery and Vaccine Development
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.
Advances in Deep Learning for Medical Image Analysis
This reference text introduces the classical probabilistic model, deep learning, and big data techniques for improving medical imaging and detecting various diseases. The text addresses a wide variety of application areas in medical imaging where deep learning techniques provide solutions with lesser human intervention and reduced time. It comprehensively covers important machine learning for signal analysis, deep learning techniques for cancer detection, diabetic cases, skin image analysis, Alzheimer’s disease detection, coronary disease detection, medical image forensic, fetal anomaly detection, and plant phytology. The text will serve as a useful text for graduate students and academic researchers in the fields of electronics engineering, computer science, biomedical engineering, and electrical engineering.
