Multimodal Deep Learning System for Nutritional Deficiency Assessment and Dietary Recommendation

Multimodal Deep Learning System for Nutritional Deficiency Assessment and Dietary Recommendation mainly focuses on to detect and analysis nutritional deficiencies by using cutting-edge AI techniques. Users can identify any deficiencies in their body through provide some images and answers some questions on their own. It acts as a doctor who examine your body and give some diet plan to follow. This system trained on multi-dataset which is consist of Text data (such as Questionnaire Dataset, Diet Recommendation Dataset), labeled image dataset (such as images of body parts such as skin, tongue, nails, eyes) as well as blood reports. The system can detect age and gender specific nutrient deficiency. This system uses deep learning models for detection of nutrient deficiencies and give recommendation for diet plan. This multimodal especially helpful for dietitians, healthcare professionals and people looking for individualized nutrition guidance. This system demonstrates that multimodal systems have potential to change traditional methods in healthcare. The Multimodal Nutritional Deficiency Assessment and Dietary Recommendation System is innovative due to its multiple datasets which include pathology reports and text-based inputs like answers to questionnaires and visual data like images of parts of the body. In this way, it presents an all-inclusive and personalized investigation of nutritional deficiencies.