Medical chatbot interface for large language models
In recent years, there has been a growing strain on accident and emergency departments in hospitals, often causing nurses and doctors to be overworked. Hence, there is a need to streamline and optimise healthcare services. This project addresses this challenge with a chatbot interface designed to...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/174530 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | In recent years, there has been a growing strain on accident and emergency
departments in hospitals, often causing nurses and doctors to be overworked. Hence,
there is a need to streamline and optimise healthcare services. This project addresses
this challenge with a chatbot interface designed to tackle patient inquiries and provide
simple medical advice. The key focus lies in the maintenance of personal data privacy
while still providing personalised responses.
The chatbot interface, implemented in Python, leverages open-source libraries like
Chainlit and LangChain to seamlessly integrate large language models(LLMs) with a
user-friendly interface. By using a LLM, the chatbot can tap into the collective
knowledge of diverse healthcare datasets. Patients can ask a wide range of medical
questions, receive relevant advice, and gain insights into their health concerns without
adding to the load of accident and emergency departments.
The implementation details including the integration of Chainlit and LangChain are
presented in this report, demonstrating the feasibility and effectiveness of the proposed
chatbot interface. |
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