The Android app uses Bluetooth-communicable smart insoles and an LSTM-based prediction model to help diabetic patients prevent injuries from turning into ulcers, with a recall rate of 90% and a precision rate of 89%.
An android based mobile app integrated with Bluetooth communicable smart insole developed for diabetic patients to prejudge injuries before they turn into ulcers. LSTM based prediction model and the app was designed by me with 90% recall and 89% precision.
This project has been maintained on Private Repo.
This project aims to predict the risk of customer support tickets escalating, in order to help organizations manage their support more efficiently and improve the customer experience.
