https://github.com/sabaimran/disease-finder

A minimal web application which allows you to look up diseases based on symptoms.
https://github.com/sabaimran/disease-finder

disorder-prediction flask health healthtech python react

Last synced: 10 days ago
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A minimal web application which allows you to look up diseases based on symptoms.

• Host: GitHub
• URL: https://github.com/sabaimran/disease-finder
• Owner: sabaimran
• Created: 2022-06-21T08:04:59.000Z (over 2 years ago)
• Default Branch: master
• Last Pushed: 2022-06-29T13:23:45.000Z (over 2 years ago)
• Last Synced: 2024-10-11T18:56:45.243Z (about 1 month ago)
• Topics: disorder-prediction, flask, health, healthtech, python, react
• Language: Python
• Homepage:
• Size: 284 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Probably Genetic - Coding Challenge

See [challenge.md](challenge.md) for the challenge description.

## Solution

Hi! You can see the solution [here](http://ec2-52-88-42-74.us-west-2.compute.amazonaws.com:3000). Click on `symptoms` to see a page which allows you to search for symptoms, select them, and then compute the most likely diagnosis. Click on `disorders` to see a flat list of all the disorders available in the database.

### Edge Cases and Future Directions

- Add provisions around data quality issues

- Add more data sources (e.g. [SNOMED](http://snomed.info/sct))

- In the UI, make it more apparent why a particular disease was in the returned list, and give a probability estimate

- Use Machine Learning to build a better algorithm for computing the most likely diagnosis

- Use a proper database more suitable for large applications (Postgres, MySQL, etc.)

- Pull more descriptive data into the database from a third party API for each disorder

- Make the disorders and symptoms more searchable - use a search bar which leverages NLP for more approximate query matching

- Use caching to improve load times, especially since the data is relatively static

- Fix the favicon. Haven't figured out how to get it to refresh.

- Use a single `docker-compose` file for setup and deployment

## Run Unit Tests

`python3 -m pytest`

## Local Development

### If using Docker Compose (preferred)

#### Prerequisites

- `sudo apt install docker-compose` ; Ensure you have docker-compose installed.

Open two separate terminals, one to run the server and one to run the client.

#### Run the client

`cd disease-finder/client && docker-compose up`

#### Run the server

`cd disease-finder/server && docker-compose up`

### If using local development (for Ubuntu 22.04)

#### Prerequisites

- `node --version` > v16.15.1

- `yarn --version` > v1.22.15

- `sudo apt install python3.10-venv` # Ensure you have python3.10-venv installed to properly setup the virtual environment.

#### Run the client

1. `yarn install`

2. `yarn start`

#### Run the server

1. `chmod +x run.bash`

2. `./run.bash`

If you're testing in this way and need to re-start the server, please comment out the db initialization step in `run.bash` to save yourself 30 minutes 😊.

## Stack

- React - frontend

- Flask - API

- sqlite - database

- SQLAlchemy - ORM