AI Powered Health Assistant for a Healthcare Agency

Understanding the Data:
The first step involved was to understand the data by analyzing the comprehensive dataset of medical records, symptoms, and corresponding diagnoses. Additionally, we required a dataset of non-medical messages that the chatbot might receive. The dataset was ensured to be diverse and representative of different age groups, genders, and health conditions. The data was preprocessed to remove any irrelevant information and to standardize the format.

Research and Development:
In the next step, we did R&D of the state-of-the-art models for generative AI. We analyzed the various machine learning, deep learning and natural language processing algorithms, to identify the suitable approach. We also did experiments with different models and architectures to optimize the chatbot’s performance.
We build various custom AI-based pipeline to be used in the chatbot: