Smart Medical Notes Generator
A web app that generates structured medical notes from keywords and PDFs using an LLM, with text, numeric, graph, and flowchart outputs.
Smart Medical Notes Generator is an online tool that aims to assist medical professionals, researchers, and students by summarizing salient points from medical literature. The system, powered by an open-source LLM, takes user-uploaded PDFs and keyword inputs as input and produces formatted notes. The output notes are provided in a variety of formats, such as text summaries, numeric data, graphical views, and flowcharts. The program maintains medical documentation efficiency through real-time previewing and downloadable reports.
Users can contribute their own medical books or research papers to further sharpen the accuracy of generated notes. The system uses user-input medical terms to pull relevant information and present it in a structured format. The project is entirely open-source, following FOSS guidelines, allowing it to be used for community-led improvements.
Technology Stack:
The backend is developed using FastAPI (Python) and combines libraries like PyPDF2 to process documents, an open-source LLM for extracting text, Matplotlib to visualize data, and NetworkX to create flowcharts. The frontend is done using ReactJS with Tailwind CSS for easy user interaction. PostgreSQL is used as the database to save uploaded documents and produced notes. Docker and Nginx are utilized to deploy the application, with GitHub Actions performing CI/CD for easy updates.
User Workflow:
Users begin by uploading medical PDFs or typing in specific keywords. The input is processed by the system through an LLM to extract structured content. The notes are generated in different formats, such as text, graphs, and flowcharts. Users can view, edit, and download the notes as a formatted PDF, streamlining medical documentation and study procedures.
Use Cases:
The tool is useful for medical students who must abstract textbooks, physicians creating structured patient notes, and researchers working with large amounts of medical literature. Through automating note-taking and generating structured output, the tool increases productivity in medical data organization.