The code on the repo is not the most updated version, the most up-to-date version of the project includes secrets, mail API requests and config data that could not be uploaded here for privacy reasons. Front-end CSS and QoL changes were also fleshed out and updated ONLY on the deployment server.
Deployed at: pyMD
Description:
pyMD is an innovative AI-driven medical diagnosis project aimed at revolutionizing healthcare by leveraging the power of machine learning and data science. Focused on predictive modeling, the project seamlessly integrates Thompson Sampling techniques to guide users through optimal lines of questioning. Utilizing the DDXplus Dataset, it incorporates Random Forest Classification to predict diseases based on user-inputted medical data. The system, featuring a Flask API, offers a user-friendly web-based GUI, enhancing accessibility and interaction. Its adaptive nature ensures continuous learning, providing precise and evolving medical diagnoses, making pyMD a cutting-edge solution at the intersection of machine learning, data science, and healthcare decision support.
What pyMD has to offer:
-
Precision in Diagnosis:
- By employing Thompson Sampling and Random Forest Classification, pyMD aims to achieve a high level of precision in medical diagnoses, aiding healthcare professionals in decision-making processes.
-
User-Friendly Interface:
- The system's Flask API ensures accessibility, making it easy for users to interact with the system and receive accurate and timely diagnostic predictions.
-
Continuous Learning:
- pyMD's adaptive nature allows it to learn and improve over time, ensuring that it stays up-to-date with the latest medical information and diagnostic trends.