Biomarker-based deep learning for personalized nutrition
Dimitrios P. Panagoulias, Dionisios N. Sotiropoulos, George A. Tsihrintzis
Abstract
In the digital era, disease diagnosis and patient management is taking a decisive leap forward to dynamically link personalized medical decision making, disease recognition and management with the massive individuality and uniqueness of the human body. Individual needs are recognised and associated with unique individual demands and tastes via automated processes and the pre-processing power of complex and accurate recom-mender systems. The gigantic pool of biometrics and biomarkers are used to predict outcomes and identify patterns in patients in an individualized manner. In this paper, we continue and improve upon recent previous work of ours [1] and develop software systems for personalized nutrition based on biomarkers and deep learning algorithms. Evaluation on real data demonstrates the high performance of our approach.