What it does
It looks at the intake of food more accurately and not just by its category. A glass of wine a day is doctor recommended while a bottle a day is not. It will average not just how many bottles are purchased but how often the purchase is done. It can also count the calories, cholesterol and vitamins, .... through out the years based on the labeling of the product.
How I built it
Using data sets from open data sources for grocery shopping of individuals and possible training of data from IBM Watson's natural language classification API.
The consumption of the food that is repeated through out the the receipts, irregular or one off items are ignored, will be averaged out to see how healthy and consistent the clients diet has been. Based on how close it meets the recommended daily recommendations for dietary supplements, it ranks the client with a grade.
Challenges I ran into
Finding appropriate data sets as well as hacking the API.
What I learned
Much better understanding of IBM Watson APIs and using them.
What's next for Risk Analyzer
Once a real sample data set is found, I will try evaluating the candidates using python and the API.
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