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Use a Bayesian evidence synthesis approach to influenza burden estimation, using hospital surveillance data.
😷Weekly Surveillance Summary of U.S. COVID-19 Activity
An R package for analyzing censored and under-reported surveillance data.
Maps of Covid-19 cases
Worked with Dr. Timothy Wiemken and Dr. Chris Prener from Saint Louis University to develop a Shiny application for COVID-19. Highlights include: anomaly and breakout detection, GIS tabs displaying health data in Missouri, and the ability to upload your own data to be analyzed.
Predictive model for the COVID-19 outbreak
COVID-19 mortality and demographic mortality laws
A Bayesian Approach to Improving Spatial Estimates After Accounting for Misclassification Bias in Surveillance Data for COVID-19 in Philadelphia, PA.
Code accompanying "Cultural Evolution, COVID-19, and Preparing for What’s Next"
Development of an R package for using colour palettes following March 2018 ECDC guidelines for presentation of surveillance data
R package with modeling, forecasting, and early detection & early warning alerts code for EPIDEMIA forecasting reports. The Epidemic Prognosis Incorporating Disease and Environmental Monitoring for Integrated Assessment (EPIDEMIA) Forecasting System is a set of tools coded in free, open-access software, that integrate surveillance and environmental data to model and create short-term forecasts for environmentally-mediated diseases. For producing formatted reports, see also the demo project based on malaria in Ethiopia (with demo data): https://github.com/EcoGRAPH/epidemiar-demo
Demo R project to be used with package epidemiar for environmentally mediated disease modeling and forecasting, integrating data from epidemiological surveillance & environmental drivers. Demo is for malaria in Amhara region, Ethiopia. Epidemiological data are artificial and should not be used for research or public health. Find epidemiar here: https://github.com/EcoGRAPH/epidemiar
ECDC in collaboration with Epiconcept developed an R package for monitoring infectious disease surveillance data
Machine learning classification models for predicting fraud transaction
R Shiny application to view weekly influenza surveillance data
Hidden Markov Model for influenza sentinel surveillance
Computational surveillance of pneumonia and influenza mortality in FluView uses epidemic thresholds to identify high mortality rates but is limited by statistical issues such as seasonality and autocorrelation. We utilized time series anomaly detection to improve recognition of high mortality rates. Results suggest anomaly detection may complement mortality reporting. Constructed with assistance from Dr. Timothy Wiemken from Saint Louis University.
Supplementary R package for the book chapter "Forecasting Based on Surveillance Data"
For empowering community 🌱
An R package to calculate probability of freedom from disease in a population based on surveillance data
Environmental Surveillance Results for PPLB
Identified which Enron employees are more likely to have committed fraud using machine learning and public Enron financial and email data.
A R package for the implementation of ICD-10-CM injury matrix
identify fraud from Enron financial data set
Some experiments about Machine Learning
A shiny-based web application for disease surveillance
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.