Northeastern researchers investigate the impact of “ultra-processed foods” on human health through the Foodome project, utilizing the FoodProX machine learning algorithm to predict food processing levels in the U.S. food supply.
They have developed FoodProX, a machine learning algorithm that accurately predicts food processing levels in the U.S. food supply. FoodProX utilizes nutritional labeling data from the USDA to assess processing in food products. Users can try the algorithm on the TrueFood research project’s website to obtain food processing scores ranging from 0 to 100. By using FoodProX, researchers bridge gaps in the dietary studies database, classify complex recipes, and gain a deeper understanding of processed foods. This tool is a significant advancement, providing valuable insights into the extent of food processing and its health implications.
Original Article Northeastern Global News
