| 书目名称 | Epidemic Analytics for Decision Supports in COVID19 Crisis |
| 编辑 | Joao Alexandre Lobo Marques,Simon James Fong |
| 视频video | |
| 概述 | Presents data analytics models used during the Covid-19 pandemic.Compares the efficacy of the models discusses, and their limitations.Relevant to those in healthcare industries and academia |
| 图书封面 |  |
| 描述 | 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.. |
| 出版日期 | Book 2022 |
| 关键词 | Analytics Models; Decision Support; COVID19 Crisis; Epidemiologic Models; Compartmental Simulation Model |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-95281-5 |
| isbn_softcover | 978-3-030-99021-3 |
| isbn_ebook | 978-3-030-95281-5 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
发表于 2025-3-21 18:24:06
