TY - BOOK TI - Predictive Models for Decision Support in the COVID-19 Crisis AU - Marques, João Alexandre Lobo AU - Gois, Francisco Nauber Bernardo AU - Xavier-Neto, Jose AU - Fong, Simon James T2 - SpringerBriefs in Applied Sciences and Technology AB - COVID-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting the virus, enormously tap into the power of artificial intelligence and its predictive models for urgent decision support. This book showcases a collection of important predictive models that used during the pandemic, and discusses and compares their efficacy and limitations. Readers from both healthcare industries and academia can gain unique insights on how predictive models were designed and applied on epidemic data. Taking COVID19 as a case study and showcasing the lessons learnt, this book will enable readers to be better prepared in the event of virus epidemics or pandemics in the future. DA - 2021/// PY - 2021 LA - en PB - Springer International Publishing SN - 978-3-030-61912-1 UR - https://www.springer.com/gp/book/9783030619121 Y2 - 2021/01/29/07:53:53 ER - TY - BOOK TI - Epidemic analytics for decision supports in COVID19 crisis A3 - Lobo Marques, Joao Alexandre A3 - Fong, Simon AB - 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. CY - Cham, Switzerland DA - 2022/// PY - 2022 DP - K10plus ISBN SP - 158 LA - eng PB - Springer SN - 978-3-030-95281-5 978-3-030-95280-8 UR - https://link.springer.com/book/10.1007/978-3-030-95281-5#about-this-book ER - TY - BOOK TI - Computerized Systems for Diagnosis and Treatment of COVID-19 A3 - Lobo Marques, Joao Alexandre A3 - Fong, Simon James CY - Cham DA - 2023/// PY - 2023 DP - DOI.org (Crossref) LA - en PB - Springer International Publishing SN - 978-3-031-30787-4 978-3-031-30788-1 UR - https://link.springer.com/10.1007/978-3-031-30788-1 Y2 - 2023/10/10/04:35:42 KW - Artificial Intelligence KW - Biofeedback KW - Computerized Diagnostic Support KW - Covid-19 KW - Signal and Image Processing ER -