Systematic review reveals multiomics and machine learning enhance understanding of nutrition’s role in cancer, suggesting robust potential for healthcare applications.
Key Points
Multiomics and AI integration enhances understanding of cancer's nutritional and metabolic factors.
Pooled AUC of 0.81 and OR of 2.4 indicate strong diagnostic and predictive capabilities in cancer.
42 studies included, showcasing diverse cancer types and metabolic signatures in treatment.
Developed translational algorithm aims to integrate nutrition and oncology in low-resource healthcare settings.