Bøger af Simon James Fong

This book describes the application of signal and image processing technologies, artificial intelligence, and machine learning techniques to support Covid-19 diagnosis and treatment. The book focuses on two main applications: critical diagnosis requiring high precision and speed, and treatment of symptoms, including those affecting the cardiovascular and neurological systems.The areas discussed in this book range from signal processing, time series analysis, and image segmentation to detection and classification. Technical approaches include deep learning, transfer learning, transformers, AutoML, and other machine learning techniques that can be considered not only for Covid-19 issues but also for different medical applications, with slight adjustments to the problem under study.The Covid-19 pandemic has impacted the entire world and changed how societies and individuals interact. Due to the high infection and mortality rates, and the multiple consequences of the virus infection in the human body, the challenges were vast and enormous. These necessitated the integration of different disciplines to address the problems. As a global response, researchers across academia and industry made several developments to provide computational solutions to support epidemiologic, managerial, and health/medical decisions. To that end, this book provides state-of-the-art information on the most advanced solutions.

Covid-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting against the virus, enormously tap on the power of AI and its data analytics models for urgent decision supports at the greatest efforts, ever seen from human history. This book showcases a collection of important data analytics models that were used during the epidemic, and discusses and compares their efficacy and limitations.Readers who from both healthcare industries and academia can gain unique insights on how data analytics models were designed and applied on epidemic data. Taking Covid-19 as a case study, readers especially those who are working in similar fields, would be better prepared in case a new wave of virus epidemic may arise again in the near future.

This book presents the combined proceedings of the 11th International Conference on Computer Science and its Applications (CSA 2019) and the 14th KIPS International Conference on Ubiquitous Information Technologies and Applications (CUTE 2019), both held in Macau, China, December 18-20, 2019.The aim of these two meetings was to promote discussion and interaction among academics, researchers and professionals in the field of ubiquitous computing technologies.These proceedings reflect the state of the art in the development of computational methods, involving theory, algorithms, numerical simulation, error and uncertainty analysis and novel applications of new processing techniques in engineering, science and other disciplines related to ubiquitous computing.

This book examines how the wonders of AI have contributed to the battle against COVID-19.