Fine-Grained Image Classification: The Purine and Alcohol Intake Awareness over Foods and Drinks for Gout Patients

We propose a way to prevent Gout by introducing a method of food image classification that supports detecting rich-purine and alcohol products. We contribute to classifying foods according to their purine and alcohol levels. Hence, the method reduces the chances of hyperuricemia for Gout patients by not consuming them. We investigate the purine and alcohol levels in the food by literature. Our method helps the Gout patient asses the containment in the foods before consuming them. The preliminary results from the research achieved 88.33% accuracy performance. The proposed research is more scientifically documented through a manuscript than similar commercial applications. Hence, its development process and performance are transparent, reliable, repeatable and scientifically proven. This research proposes using Deep Learning to improve the Gout disease problem.