PyRoss: inference, forecasts, and optimised control of epidemiological models in Python. github.com/rajeshrinet/pyross
An AI, Machine Learning and Blockchain based healthcare ecosystem that predicts health outcome, divulges users' and environmental health risk; mitigates illicit drug use.
Deep Learning for Epidemiological Predictions
Epidemiologically and Socio-economically Optimal Policies via Bayesian Optimization
Agent-based modelling of pandemics using the Susceptible, Infected, Recovered (SIR) framework.
YouTube Video Viralization Tool: a mathematical tool to optimize efforts of making viral youtube videos.
📈 Examination of the impact of COVID-19 spread by using a custom epidemiological model.
Projet d'année 3 transdisciplinaire du groupe 1.
Modelling the spread of COVID-19 in India
D-FENSE project deals with Dengue Virus (DENV) epidemics in Brazil, enabling predictive modeling and data visualization to support decision-making in public health.
DeepAR implementation for seasonal influenza cases in German districts
CLiDENGO26-Chikungunya is a forecasting model for Chikungunya dynamics through a mechanistic, stochastic climate-modulated β-logistic growth model for weekly chikungunya cases at the state (UF) level.
Predicting early treatment departure risk in tuberculosis patients using a Bayesian-optimized XGBoost model on clinical data from the Philippines.
machine learning with python
Modeling and forecasting COVID-19 case trends using time-series data, polynomial regression, and cross-validation for multiple countries.
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.
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