PyRoss: inference, forecasts, and optimised control of epidemiological models in Python. github.com/rajeshrinet/pyross

Deep Learning for Epidemiological Predictions

An AI, Machine Learning and Blockchain based healthcare ecosystem that predicts health outcome, divulges users' and environmental health risk; mitigates illicit drug use.

Epidemiologically and Socio-economically Optimal Policies via Bayesian Optimization

Agent-based modelling of pandemics using the Susceptible, Infected, Recovered (SIR) framework.

📈 Examination of the impact of COVID-19 spread by using a custom epidemiological model.

Projet d'année 3 transdisciplinaire du groupe 1.

YouTube Video Viralization Tool: a mathematical tool to optimize efforts of making viral youtube videos.

Modelling the spread of COVID-19 in India

DeepAR implementation for seasonal influenza cases in German districts

D-FENSE project deals with Dengue Virus (DENV) epidemics in Brazil, enabling predictive modeling and data visualization to support decision-making in public health.

SARS-CoV-2 disease model

Predictive modeling of cholera severity in the Gedeo Zone, Ethiopia, using epidemiological and clinical data. This notebook applies machine learning techniques, including feature engineering, Bayesian hyperparameter optimization, and classification with XGBoost and Random Forest.

machine learning with python

Modeling and forecasting COVID-19 case trends using time-series data, polynomial regression, and cross-validation for multiple countries.

Predicting early treatment departure risk in tuberculosis patients using a Bayesian-optimized XGBoost model on clinical data from the Philippines.