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The COVID-19 pandemic represents the most significant public health disaster since the 1918 influenza pandemic. During pandemics such as COVID-19, timely and reliable spatio-temporal forecasting of epidemic dynamics is crucial. Deep…

机器学习 · 计算机科学 2020-11-25 Lijing Wang , Aniruddha Adiga , Srinivasan Venkatramanan , Jiangzhuo Chen , Bryan Lewis , Madhav Marathe

The COVID-19 pandemic has had a considerable impact on day-to-day life. Tackling the disease by providing the necessary resources to the affected is of paramount importance. However, estimation of the required resources is not a trivial…

图像与视频处理 · 电气工程与系统科学 2022-05-11 Sai Vidyaranya Nuthalapati , Marcela Vizcaychipi , Pallav Shah , Piotr Chudzik , Chee Hau Leow , Paria Yousefi , Ahmed Selim , Keiran Tait , Ben Irving

We introduce DeepGLEAM, a hybrid model for COVID-19 forecasting. DeepGLEAM combines a mechanistic stochastic simulation model GLEAM with deep learning. It uses deep learning to learn the correction terms from GLEAM, which leads to improved…

机器学习 · 计算机科学 2021-03-24 Dongxia Wu , Liyao Gao , Xinyue Xiong , Matteo Chinazzi , Alessandro Vespignani , Yi-An Ma , Rose Yu

Purpose: Artificial intelligence (AI) techniques have been extensively utilized for diagnosing and prognosis of several diseases in recent years. This study identifies, appraises and synthesizes published studies on the use of AI for the…

COVID-19 continues to cause a significant impact on public health. To minimize this impact, policy makers undertake containment measures that however, when carried out disproportionately to the actual threat, as a result if errorneous…

Background: To assist policy makers in taking adequate decisions to stop the spread of COVID-19 pandemic, accurate forecasting of the disease propagation is of paramount importance. Materials and Methods: This paper presents a deep learning…

社会与信息网络 · 计算机科学 2020-09-28 Ahmed Ben Said , Abdelkarim Erradi , Hussein Aly , Abdelmonem Mohamed

The advent of the COVID-19 pandemic has instigated unprecedented changes in many countries around the globe, putting a significant burden on the health sectors, affecting the macro economic conditions, and altering social interactions…

物理与社会 · 物理学 2020-07-23 Dmitry Gordeev , Philipp Singer , Marios Michailidis , Mathias Müller , SriSatish Ambati

COVID-19 has challenged health systems to learn how to learn. This paper describes the context, methods and challenges for learning to improve COVID-19 care at one academic health center. Challenges to learning include: (1) choosing a right…

In late 2019, COVID-19, a severe respiratory disease, emerged, and since then, the world has been facing a deadly pandemic caused by it. This ongoing pandemic has had a significant effect on different aspects of societies. The uncertainty…

神经与进化计算 · 计算机科学 2021-09-28 Mahdi Rahbar , Samaneh Yazdani

COVID-19 as a global pandemic causes a massive disruption to social stability that threatens human life and the economy. Policymakers and all elements of society must deliver measurable actions based on the pandemic's severity to minimize…

社会与信息网络 · 计算机科学 2024-06-12 Shuo Yu , Feng Xia , Yueru Wang , Shihao Li , Falih Febrinanto , Madhu Chetty

The COVID-19 pandemic has caused millions of cases and deaths and the AI-related scientific community, after being involved with detecting COVID-19 signs in medical images, has been now directing the efforts towards the development of…

图像与视频处理 · 电气工程与系统科学 2026-03-13 Valerio Guarrasi , Paolo Soda

Effective epidemic modeling is essential for managing public health crises, requiring robust methods to predict disease spread and optimize resource allocation. This study introduces a novel deep learning framework that advances time series…

图像与视频处理 · 电气工程与系统科学 2026-01-19 Mousa Alizadeh , Mohammad Hossein Samaei , Azam Seilsepour , Alireza Monavarian , Mohammad TH Beheshti

The COVID-19 pandemic has inspired unprecedented data collection and computer vision modelling efforts worldwide, focusing on diagnosis and stratification of COVID-19 from medical images. Despite this large-scale research effort, these…

计算机视觉与模式识别 · 计算机科学 2021-06-01 Michael J. Horry , Subrata Chakraborty , Biswajeet Pradhan , Maryam Fallahpoor , Chegeni Hossein , Manoranjan Paul

The Covid-19 pandemic has been one of the most devastating events in recent history, claiming the lives of more than 5 million people worldwide. Even with the worldwide distribution of vaccines, there is an apparent need for affordable,…

Pandemic control measures like lock-down, restrictions on restaurants and gatherings, social-distancing have shown to be effective in curtailing the spread of COVID-19. However, their sustained enforcement has negative economic effects. To…

This study investigated the performance, explainability, and robustness of deployed artificial intelligence (AI) models in predicting mortality during the COVID-19 pandemic and beyond. The first study of its kind, we found that Bayesian…

机器学习 · 计算机科学 2023-11-30 Jacob R. Epifano , Stephen Glass , Ravi P. Ramachandran , Sharad Patel , Aaron J. Masino , Ghulam Rasool

The COVID-19 pandemic is considered as the most alarming global health calamity of this century. COVID-19 has been confirmed to be mutated from coronavirus family. As stated by the records of The World Health Organization (WHO at April 18…

人工智能 · 计算机科学 2023-11-03 Subhrangshu Adhikary , Sonam Chaturvedi , Sudhir Kumar Chaturvedi , Saikat Banerjee

Because of the rapid spread of COVID-19 to almost every part of the globe, huge volumes of data and case studies have been made available, providing researchers with a unique opportunity to find trends and make discoveries like never…

机器学习 · 计算机科学 2021-10-20 Sarwan Ali , Yijing Zhou , Murray Patterson

We propose a novel approach that integrates machine learning into compartmental disease modeling to predict the progression of COVID-19. Our model is explainable by design as it explicitly shows how different compartments evolve and it uses…

With COVID-19 affecting every country globally and changing everyday life, the ability to forecast the spread of the disease is more important than any previous epidemic. The conventional methods of disease-spread modeling, compartmental…

机器学习 · 统计学 2022-08-19 Benjamin Lucas , Behzad Vahedi , Morteza Karimzadeh
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