A Novel Machine Learning and Deep Learning Driven Prediction for Pre-diabetic Patients
Sahil Shahakar, Priyal Chopde, Neha Purohit, Anushka Vishwakarma, Aditi Nite, Ashish K. Sharma
Abstract
Of late there has been a considerable rise in pre-diabetic patients. Pre-diabetic patients need to keep a watchful eye on their sugar intake to avoid blood sugar spikes. Fruit is an important source of vitamins, minerals, and fiber. However, fruit can also be high in sugar. Thus it is strongly needed to check if the fruit is safe for consumption from the blood sugar perspective. The Glycemic Index (GI) is a measure of the rise in blood sugar levels after eating a particular food. Blood sugar spike is caused by the rapid absorption of sugar into the bloodstream, which can be slowed down by consuming dietary fiber along with the fruit. This research proposes a Machine Learning and Deep Learning based prediction model that can predict the glycemic index of fruits using images, and suggest if the fruit is safe for consumption. For image recognition and classification it uses Convolutional Neural Network (CNN). In addition, it provides the user with food recommendation with high dietary fiber to create balanced diet if necessary.