Transforming Diabetes Management through LSTM Models,OCR And AI Chatbot

Through the creation of an integrated system that blends optical character recognition (OCR) technology with a chatbot driven by long short-term memory, this project tackles the rising problem of managing diabetes. The system classifies people as prediabetic or diabetic by allowing patients to input their diabetic test results. This allows the system to extract important health indicators, including HbA1c values. Patients with diabetes get evaluations of other health indicators, such as HDL and VLDL levels, which alert them to the need for additional medical consultations, while patients with prediabetes receive tailored nutritional suggestions to promote healthier lifestyle choices. Adding voice interaction features improves accessibility and facilitates user interaction with the chatbot. Users may monitor their health by using a web-based application that visualizes health data. It also provides multiple logins where the care-taker of a patient can also access the patient’s data