Healthcare for Humanity

LibreHealth is the foundation of a worldwide ecosystem of open source Health IT innovation and is a place where people can come together to build tools that enhance the quality of healthcare around the world.

We currently have under our umbrella the following projects:

  • LibreHealth Toolkit, a foundational base for building Health IT tools
  • LibreHealth EHR, an electronic health record derived from best practices and technology from leading open source systems
  • LibreHealth Radiology, a specialized distribution of LibreHealth Toolkit customized for radiology health care professionals

Our GSoC student projects will address the real-life needs of our projects to help improve the delivery of health care around the world. We have a team of expert mentors with decades of experience to help you in your work. They will be continually adding project ideas to our forum, and we encourage you to suggest ideas too as you learn more about our projects.

lightbulb_outline View ideas list

Technologies

  • java
  • javascript
  • python 3
  • android
  • php

Topics

comment IRC Channel
email Mailing list

LibreHealth 2020 Projects

  • Prajwal S Belagavi
    Android application to show birth registration and newborn health data
    This project aims to develop an Android application for mothers and guardians of newborn babies in Kenya to receive and display birth information and...
  • Kislay Kunal Singh
    Automatic labelling of Radiology Images
    A web app that does automatic labeling of radiology images. The backend is in Django and tensorflow-serving whereas the frontend is in Reactjs. The...
  • Darshpreet Singh
    Develop an Android mobile application to show patient friendly costs of care
    To make an app which can display costs of medical procedures of US hospitals & a web scraper which can scrape ChargeMasters & update data...
  • Aishwarya Harpale
    Low Powered Models for Disease Detection and Classification for Radiology Images
    The goal of this project is to develop models and train them on various Radiology images. These models need to be made suitable to be run on low...
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2020