Visit the Website

Checkout the application live at http://amiga.pythonanywhere.com

Inspiration

Environmental impact caused by sanitary waste generated by us women is one of the significant topics in discussions today. A plastic, industrially manufactured, disposable sanitary pad requires about 500–800 years to decompose. Thousands of tons of disposable sanitary waste is generated every month all over the world. While women health is important, however we as women need to take on the responsibility of reversing this environmental damage caused by us.

Women health and environmental protection are linked together. Because of women’s relationship with the environment, they can be critical agents of environmental conservation, sustainable development and adaptation to climate change.

What it does

The name of my hack is AMIGA which means "female friend" in spanish. Amiga is a one-stop solution for every women to look after their health while protecting the environment. This website is here to help women analyze their lifestyle and menstrual health in an eco-friendly manner keeping the environment clean and green.

This website brings together multiple ways by which women can look after their health while protecting the environment. Some of the features of this web application includes ML-based female health assessments like PCOS Risk prediction test, Lifestyle Assessment etc., some ideas for protection of the environment like Plant your own Tree Initiative, Menstrual Cup Usage Awareness Initiative etc., along with a lot of resources for women to maintain their reproductive and general health.

Features Provided

  • Lifestyle Assessment : A healthy lifestyle is one which helps to keep and improve our health and well-being. But in the chaos of a woman's daily life, healthy living may take back seat to chores. To tackle such situations, I have developed a lifestyle assessment based on the multiple online resources. This assessment will help women analyse their lifestyle choices in depth and will help them highlight some of the flaws in their current lifestyle.

  • PCOS Risk Prediction Test : PCOS (Polycystic ovarian syndrome) is a common health problem caused by an imbalance of reproductive hormones. It is estimated that 3 out of every 10 women today have PCOS. Women of all races and ethnicities are at risk of PCOS. Your risk of PCOS may be higher if you have some specific symptoms. So, based on some common symptoms and related datasets, I have developed this ML-based PCOS Risk Prediction Test which will inform women whether they are at risk of suffering from PCOS or not so that women at risk can get their clinical checkup done at the earliest and can start their treatment in case the results are positive.

  • Plant your own Tree Initiative : For all the sanitary waste we all women have created in our lives so far, lets pledge to plant trees to compensate all the environmental destruction caused by us. This website tends to provide a way for each one of you to plant trees through our platform by just clicking a button from the comforts of your home. User just have to select a location where they want to plant their tree and they also need to donate some amount to support our volunteers who will be planting the trees. And it's done! Within the next 24 hours the tree will be planted at the selected location and the user will be able to see the live pictures of the tree growing!

  • Menstrual Cup Usage Awareness Initiative : This website discusses about the importance of menstrual cups in protecting the environment and tried to encourage women to start using menstrual cups. This website also provides links from where women can purchase these cups.

  • Women Health Resources : This website provides multiple resources for women to maintain their health and well being. Some of the resources includes PCOS related videos, Self breast examination etc.

How I built it

I have used Python and Flask API to build the web application. I have used Google Cloud APIs to embed a map and get the location of the user for the "Plant Your Own Tree" feature. I have used women health information from various online resources in order to spread awareness amongst women.

For the PCOS Risk Detection Test, I have used a dataset available on Kaggle which contains data from 10 different hospitals across Kerala, India. The dataset contains all physical and clinical parameters to determine PCOS. However, I have used only those parameters which can be easily recognized by an individual without much clinical help. The dataset size is however small, only 542 rows. In order to train this model, I first performed some data processing in order to remove the extra parameters and manage missing values. I have used Random Forest classification algorithm to train a model.

Technologies Used includes:

  • Python : Python is the programming language in which the ML model for PCOS detection is has been built.
  • Flask : Flask is used to build the backend of the web application.
  • Sklearn : This is the python library which is used to set up the ML random forest model.
  • Javascript, HTML and CSS : These are the technologies which have been used to create the frontend of the web application.
  • Google Cloud API : I have used Google Cloud APIs including maps and geo-encoding to embed a map and get the location of the user for the "Plant Your Own Tree" feature.
  • PythonAnywhere : This is the service which has been used to host the web application.

Challenges I ran into

Deciding about which machine learning technique to use for training the PCOS detection model was challenging.

What I learned

This was my first time building a complete Flask Application on my own, so this was a good learning experience. Also, I learnt how to use Google Cloud APIs for my website.

What's next for Amiga

In the future, I really want to make this idea into a start up. I want to eventually add many more features to the application like daily health insights and blogs on environmental protection, online fitness tools and tracker, menstrual cycle tracker and ovulation calendar and many more.

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