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Developed a Streamlit prototype for a machine learning software enabling physicians to recommend the most effective antidepressant based on a patient’s genetic makeup and demographics. Final project built for the AI4Good Lab.

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PrecisionMD

Project Description

PrecisionMD is a software that utilizes a SVM machine learning model to create a personalized medicine tool for doctors. For a patient diagnosed with depression, it predicts the top two most effective antidepressants based on their genetic makeup and demographics, to maximize treatment success rates.

Prototype Demo

Streamlit App

Usage

Navigate to the Patients page and click on the "Add Patient" button to generate a new patient entry. image

Input the patient's information and click the "Generate Report" button to see the top two recommended medications and associated top 5 drug reactions reported to the FDA.

Installation Instructions

Run it Locally

virtualenv .venv
source .venv/bin/activate
pip install -r requirements.txt
streamlit run app.py

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Developed a Streamlit prototype for a machine learning software enabling physicians to recommend the most effective antidepressant based on a patient’s genetic makeup and demographics. Final project built for the AI4Good Lab.

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