Diabetes is a chronic disease that affects the body's ability to produce or use insulin effectively. When children are diagnosed with diabetes, it can be a big issue for several reasons:
Prevalence: The incidence of diabetes in children is increasing globally. According to the World Health Organization, the number of children with type 1 diabetes is increasing by 3% each year.
Serious health risks: Diabetes can cause serious health complications if not properly managed, including cardiovascular disease, kidney damage, and nerve damage. Children with diabetes are also at higher risk of developing infections and experiencing vision problems.
Lifestyle changes: Managing diabetes requires significant lifestyle changes, including following a healthy diet, engaging in regular exercise, monitoring blood sugar levels, and taking insulin or other medications. These changes can be challenging for children and their families to navigate.
Emotional impact: Children with diabetes may feel isolated or different from their peers, leading to emotional and social challenges. They may also experience anxiety or depression related to managing their condition.
Financial burden: Diabetes can be expensive to manage, with costs including medications, supplies, and regular medical appointments. This can create a financial burden for families, particularly those without adequate health insurance.
Overall, diabetes in children is a big issue because it can have serious health consequences and requires significant lifestyle changes and management. It is important for children with diabetes to receive appropriate medical care and support to manage their condition effectively.
What it does
A web and mobile app that uses machine learning to cater custom food recommendations and meal plans for inidivduals with diabetes with artificial intelligence.
How we built it
We trained a model in python and deployed it as a web application using React JS and a mobile app using React native.
Challenges we ran into
We found that the back end for mobile applications is very complex and prone to errors. Specifically, we had to keep the design as simple in order to create basic commands and buttons in the apps.
Accomplishments that we're proud of
Managing to get our machine learning model to be implemented wthin a web application to work.
What we learned
We had to make our model more efficient and smaller for it to be of use in a mobile application.
What's next for Dietbetes
Launch it on the Google and App store so that there can be widespread access to this app for those with diabetes.