Leveraging an AI solution for processing text reviews of drugs employing ML algorithms to provide an overview of the effectiveness or adverse reactions. The distributed information in the form of blogs or specialized websites for user drug reviews has huge potential for analysis
A robust AI solution that would take this unstructured data into consideration and transform, which in turn are used by suitable algorithms to determine whether the drug will be effective or not, given review(s) of the drug.
The solution would provide an overview of the effectiveness and adverse reactions of a drug, aggregated into three distinct categories, that are, effective, ineffective and adverse.
This solution is powered by the H2O AI Cloud Driverless AI AutoML, H2O-3, and H2O.ai Wave. The data science approaches include genetic algorithm, advanced feature engineering, classification and regression algorithms, GLM, GBM, XGBoost, ensemble stacking, tf:idf, and various machine learning interpretability algorithms