A healthier world for all, by all

The Application

Think of this application as a health study on a global scale and an opportunity to be a part of something bigger than yourself. Your information and your experiences are valuable and when your information can be combined with others and analyzed; it could be tremendously valuable to others struggling with health issues or in general looking for a healthier way of life.

eWHO will be an application that will allow users to enter as much or as little information about themselves including health, lifestyle choices, demographics, and genetics; more information is better of course.

Typical studies for vitamins or medicines are conducted on a “small” sample size of the population. In doing so all variables cannot be accounted for. Usually, it is not until the products have been distributed to the general population and are being widely used that the true benefits and risks are uncovered. Benefits and risks vary greatly based on demographics, lifestyle, food choices and so on. Even upon further study, there are conflicting results where some can say there are benefits and others will see more risks.

Use Case 1

When I’m in the grocery store and I want to try a new supplement I pick up my phone, scan the barcode of a bottle of ‘Calcium’ and the application shows me potential risk vs potential benefits for me taking calcium; all based on the personal information I’ve provided and the data mining and machine learning information that the application has compiled from all the other users around the world. taking ‘Calcium’.

Use Case 2

I am sitting on the couch eating my second piece of cheesecake and start to wonder; “Would changing my diet help me out?”. I grab my phone and pop open my eWHO application and go to the “What If” section. I select a new diet like Paleo and let the application crunch the data. The application will take into consideration the data I’ve provided as well as the data of other users around the world. The application will then present some potential benefits and/or risks along with any other correlations related to the change in diet.

Technology

The application will be driven by the data provided by the users and processed using data mining and machine learning techniques.