Medical QA: A Virtual Doctor in your Pocket
Year: 2025
Type: article
Abstract: Here a Gemma-based Medical QA solution has been designed and implemented for medical questions. The answer involves cutting-edge NLP to develop an AI chatbot that’s able to provide relevant, reliable medical data in real time based on user input. The model was refined against the Malikeh Ehghaghi medical QA-dataset and fitted with a large language model (LLM). This was a distributed application with AWS SageMaker scaling inference and a Lambda function running it serverless. Then we developed an intuitive web interface with Django and modern front-end technology (HTML, CSS, JavaScript) for the seamless user experience. Medical queries and responses can be processed in real-time and users can gain access to dependable medical data. This is where the promise of fine-tuned LLMs in the healthcare field is shown, by revealing medical knowledge and symptoms that can be applied to medicine more effectively for patients and clinicians. Model problems associated with model training, deployment and integration are also described along with the potential future gains in model performance and scalability.
Author: Revel, Hassan
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W6949378616
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