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medical-data

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In this project, we propose to deal with the data scarcity problem in a specific NLP task by harnessing existing annotated datasets from related tasks. Our approach involves training a multi-head architecture concurrently on both the main task and these “supporting” tasks. We experimented this approach on medical NLP tasks and on three GLUE tasks.

  • Updated Dec 13, 2023
  • Python

This project implements a machine learning-based triage system for emergency rooms, which classifies patients based on their symptoms and vitals using a Random Forest Classifier. The system features real-time patient data integration, a user-friendly GUI built with Tkinter, and secure patient data encryption using Fernet from the cryptography lib

  • Updated Oct 21, 2024
  • Python

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