navinbondade/customizable-retrieval-based-health-chatbot-with-gui

Here in the project, I have created a retrieval-based health chatbot that answers users questions related to their health and helps in accelerating the treatment process.

Customizable Retrieval Based Health Chatbot

The recent pandemic underscored a critical issue: the ratio of available doctors to the population is alarmingly low, leading to delays in accessing healthcare. To address this challenge, I have developed a retrieval-based health chatbot designed to bridge the gap between patients and healthcare providers. This chatbot leverages advanced natural language processing techniques to accurately interpret and respond to users' health-related queries, providing timely information and guidance. By facilitating quicker access to reliable health information, this tool plays a vital role in accelerating the treatment process, ensuring that users receive the support they need in a timely manner.

Libraries Used

• Tensorflow
• Numpy
• Pandas
• Matplotlib
• Seaborn
• Sklearn
• NLTK

Methodology and Approach

I have developed an advanced neural network architecture tailored to understand and respond to a wide range of medical and health-related queries. This model, which consists of three fully connected layers, has been meticulously trained over one thousand epochs using the Stochastic Gradient Descent (SGD) optimizer. By analyzing the input queries, the network generates an intent key, which is then used to retrieve the most relevant answers. Integrated into a retrieval-based health chatbot, this system provides accurate and timely responses to users' health questions, effectively bridging the gap between patients and healthcare providers. This innovative approach not only enhances accessibility to reliable health information but also accelerates the treatment process, making it a valuable tool in addressing the pressing healthcare challenges highlighted during the pandemic.