An examination of predictive disease saliency in social networks and the potential application of network analysis in locating disease spread
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Updated
Jun 19, 2016 - Python
An examination of predictive disease saliency in social networks and the potential application of network analysis in locating disease spread
An agent-based model of infectious disease spread.
Modelisation of viruses propagation on a worldwide scale
Final Project for a Mathematical Biology course
supplementary code and data to Diehl et al, 2016 (Cell)
This repository is created as a part of an academic project for the course Model Based Decision Making EPA1361
Analysis using network theory to model interacations between doctors
Epidemic Vulnerability of a Region - Disease Prediction
A C++ program that simulates an infection through terminal ASCII characters.
A reanalysis of Semmelweis's hand-washing and child-bed fever study
An implementation of a primitive SIR model to simulate the propagation of a disease with a limited set of variables.
Disease Trends of anywhere in the World
Human Disease Network: clustering and performance evaluation. Project for the Data Analytics course @unimib18/19.
Simple simulation of epidemic disease spread.
A collection of MATLAB scripts used for a research project at the Mathematical and Theoretical Biology Institute (MTBI) 2011 Summer program.
Graph based epidemic simulations.
Series of image recognition algorithms that can diagnose diseases by analysing a picture of the iris of the person
Analysis of core Chronic Diseases in Northern Nigeria is a group project demo performed by trainees at GIZ sponsored Data Science training program by COVEN LABS. The Data was gotten from kaggle.com and was prepared by Emmanuel Odelanmi who was trying to predict Meningitis occurrence in individuals using Machine Learning. The project is to advice…
Graphically simulates the spread of disease over a population according to customizable properties such as transmission rate, transmission range, incubation/illness/convalescence period length, death rate, and virus mutation rate.
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