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About The Project

This is Team CVP's solution to NIH NCAT's Bias Detection Tools in HealthCare Challenge

Getting Started

This is an example of how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple example steps.

Prerequisites

  • Python 3.8
  • Requirments are in scripts\requirements.txt

Folder Structure

The script is using the following directory tree structure:

├── scripts/           # This is where `measure_disparity.py` and `mitigate_disparity.py` are
├── reports/           # Location for the html report generated by the script
├── input_model/       # Insert input model data here
├── output_model/      # This is where the mitigated model prediction is saved
├── data/              # Sample data to run the model 
├── js/                # javascript for the team submission landing page 
├── css/               # css files for the team submission landing page 
├── assets/            # images for the team submission landing page 

Installation

  1. Clone this repo
  2. Save a copy of the input in input_model/ as input_model.csv. input_model.csv should include one row per individuals with columns below:
* Model prediction (as a probability)
* Binary outcome (i.e. 0 or 1, where 1 indicates the favorable outcome for the individual being scored)
* Model label
* Sample weights
  1. Execute the python file python scripts\measure_disparity.py
  2. An html report will be generated in reports\measure_report.html
  3. If the report shows bias, users can mitigate the bias by running python scripts\mitigate_disparity.py
  4. Html reports will be generated in reports\mitigate_report.html and reports\imbalance_report.html

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Architecture

AI Bias Tool Architecture

License

Distributed under the BSD 3 License. See LICENSE.txt for more information.

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Contact

Project Link: https://github.com/cvp-bias-detection-healthcare/

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