NutriGaze: AI-Driven Dietary Planning with OCR and NLP

These days diabetes is among the most common diseases all over the globe. As a result, people suffering from diabetes need to change their way of life completely for the sake of their health. The health results may likely be interesting additions to overall wellness in this aspect. In this paper, we investigate the intersection of various software models including NLP and OCR for bettering diabetic dietary management. In this case, all different names given to sugar products in ingredient labels or items are indicated through natural entity recognition models by this application. This deals with two things mainly. First, it uses OCR to read text from the ingredient labels. Second, a custom NER model is advanced that establishes a threshold for the terms related to sugar. That is why the analysis can move faster and even slight occurrences of sugar or its derivatives could be detected through it. It therefore concerns about hard work between computer science and medical disciplines to minimize stress in life of patients suffering from diabetes mellitus globally.