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Logistic Regression Disease Prediction with PERN & AWS Lambda

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Medical Dashboard

This is an web application separated into two difference user types: patients and doctors. Users are authenticated using cookies, JWT, Bcrypt, and PostgresSQL

Doctors can see all the patients and see the disease that the patient is diagnosed with and prescribe a medication to send back.

Patients can select the symptoms they are feeling and submit the info to a deployed machine learning model.

It is a simple logistic regression model trained from a Kaggle dataset (https://www.kaggle.com/datasets/kaushil268/disease-prediction-using-machine-learning) using sklearn. On the small testing dataset, it achieves **100% **accuracy. The model is deployed using FastAPI, Docker, and AWS Lambda.

The frontend of the web application is done in React, with an Express.js backend, and PostgreSQL.

Originally this was a CRUD to-do app, so since this is a work in progress some of the files are remnants of the to-do app.

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