The project titled “AI-Powered Personalized Nutrition Plans: Analysis and Application of Metabolomic
Data,” led by Asst. Prof. Dr. Nursena Bayğın from the Erzurum Technical University (ETU) Department
of Computer Engineering, with Asst. Prof. Dr. Handan Akalın from the Faculty of Health Sciences
Department of Nutrition and Dietetics serving as a researcher and graduate student İlknur Akcaba
participating as a scholar, has qualified for support under the TÜBİTAK 1002-A Quick Support Program.
Within the scope of the project, it is aimed to develop AI-based personalized nutritional recommendations
by analyzing individuals' metabolomic profiles, clinical health data, and lifestyle characteristics
simultaneously. Accordingly, an innovative decision support system will be designed using deep learning
and advanced machine learning methods capable of offering nutritional recommendations tailored to
individuals' physiological characteristics.
By utilizing open-source health and metabolomic datasets, the system to be developed aims to generate
more accurate and customized recommendations through the joint evaluation of diverse data types. The
system is intended to raise awareness of healthy living, offer scientifically grounded solutions in
combating obesity and metabolic diseases, and establish an infrastructure for mobile health applications
that may be developed in the future.
Corporate Communications and Promotion Directorate – 04.06.2026