Our client wanted to develop an app to disrupt the healthcare space using technology, by helping junior doctors in rural areas improve their prescriptions for a chronic disease, based on disease progression. The app would be used to collect data on the symptoms of patients over multiple visits. They needed a model that can predict tweaks to the current prescription to provide relief from symptoms and arrest potential complications.
- Our team analyzed historical prescription data from senior doctors which were deconstructed to find the underlying patterns of medication depending on the disease progression.
- These patterns were used to create an AI model
- Model change in prescription
- Automated selection of features for predicting each potential change in prescription
- Deal with sparse data for certain prescription changes using domain insights
TECHNIQUES, TECHNOLOGIES, TOOLS
- Bayesian Structure Learning, Random Forest, Gradient Boosted Decision Trees, Dynamic Bayesian Networks
The app helped junior doctors in rural areas to be more consistent in their prescriptions, removing bias in the decision making. Thereby, improving the lives of the patients.