To achieve this purpose, we have made use of Covid-19 disease data, World vaccination and Vaccine reactions dataset that were available on Kaggle.Amrita, I.Global Academy of TechnologySen, SnigdhaIndian Institute of Information TechnologyAshwini, K....
This paper presents multiple novel findings from a comprehensive analysis of a dataset comprising 1,244,051 Tweets about Long COVID, posted on Twitter between 25 May 2020 and 31 January 2023. First, the analysis shows that the average number of Tweets per month wherein individuals self-reported...
Pseudo Algorithm Here is the algorithm for the parameters’ optimization in (A5). Algorithm A1 Adam based method for parameter optimization. Good default settings for the analyzed COVID-19 dataset are learning rate 𝜂=0.05η=0.05, exponential decay rates 𝑏1=0.1b1=0.1 and ...
Communications Medicine (2024) Safety, immunogenicity and protective effect of sequential vaccination with inactivated and recombinant protein COVID-19 vaccine in the elderly: a prospective longitudinal study Hong-Hong Liu Yunbo Xie Fu-Sheng Wang Signal Transduction and Targeted Therapy (2024)Sections...
CORD-19 Related dataset CORD-19 Related tools AWS Resources and programs supporting COVID-19 research: Google Cloud COVID-19 public dataset program 2019 COVID-19 Data Set in Korean 한국어 Dataset Image datasets Open Datasets Models
本篇的数据来源https://www.kaggle.com/gpreda/covid-world-vaccination-progress 主要信息: 国家 - 这是提供疫苗接种信息的国家; 国家ISO代码 - 国家的ISO代码; 日期 - 数据输入日期;对于某些日期,我们只有每日接种疫苗,对于其他日期,只有(累计)总数; ...
Adherence to non-pharmaceutical interventions following COVID-19 vaccination: a federated cohort study Benjamin Rader Neil K. R. Sehgal John S. Brownstein npj Digital Medicine(2024) The effect of mobility reductions on infection growth is quadratic in many cases ...
In this research work, Iapplied two different machines learning-based ensembling approaches named boosting and bagging on COVID-19 dataset obtained from Kaggle ( https://www.kaggle.com/ ) and GitHub ( https://github.com/datasets/covid-19 ). This case study uses a comparative analytical ...
Input: Train dataset, Test imageOutput: Predicted class, Quantitative Evaluation Step 1: Perform the DLCNN training procedure and develop the trained features from the train dataset. Step 2: Apply test CXR image to random under sampling-based preprocessing, so noises, size mismatches presented in ...
Critical parameters and information are described and presented for each dataset/database. For this purpose, Google Scholar, Baidu, and five reliable databases—IEEE Xplore, Web of Science, PubMed, ScienceDirect, Kaggle, and Scopus—were used to obtain pertinent studies on the given topics. The ...