Published Paper Details:

Numerous human disorders, such as Alzheimer's, Parkinson's, and type 2 diabetes, are linked to amyloid proteins. Through the regulation of Amyloid protein deposition, some foods and vegetables can assist in the prevention of certain disorders in humans. Onions, kale, tomatoes, cabbage, and romaine lettuce are examples of vegetables. Additional food items such as walnuts, coffee, berries, fatty fish, turmeric, champagne, and cinnamon also assist with the administration of illnesses brought on by the buildup of Amyloids. This experiment uses a dataset that includes the aforementioned dietary items in an attempt to predict amyloid proteins. Neural Net Analysis and Gradient Boosting Classifier are utilized in this data analysis. Under the current system, people with amyloidosis see doctors after developing the illness. Preventing is always better than curing. By forecasting the Amyloids based on dietary habits, the suggested system helps avoid the disease. By enabling people to modify their eating habits, it prevents the occurrence of amyloidosis. The project's goal is to develop a tool for Prediction of Amyloid Proteins using Gradient Boosting Model.