Skip to Content
DiseasesDiseases
  • This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
  • Review
  • Open Access

25 February 2026

Tracking the Metabolites of Health and Disease Using Artificial Intelligence

,
,
and
1
Computational Oncology Unit, University of Chicago Medicine Comprehensive Cancer Center, 900 E 57th St, KCBD Bldg., Chicago, IL 60637, USA
2
Department of Anesthesiology, Oakland University William Beaumont School of Medicine, Rochester, MI 48309, USA
3
Department of Anesthesiology, Wayne State University, Detroit, MI 48341, USA
4
Electrical and Computer Engineering, Western Michigan University, 1903 W. Michigan Ave., Kalamazoo, MI 49008, USA

Abstract

Using AI to analyze metabolite profiles provides critical insights into health, aging, and disease. Metabolomic signatures reveal how lifestyle and therapy impact organ function and cancer progression. This review highlights emerging toolkits for high-throughput data analysis, emphasizing their integration with other omics. Advanced AI approaches facilitate metabolic pathway mapping and accelerate biomarker discovery. By combining AI with multi-omics, researchers can optimize interventions and enhance precision medicine. This article serves as a resource demonstrating AI’s potential in diagnostics and drug discovery.

Article Metrics

Citations

Article Access Statistics

Multiple requests from the same IP address are counted as one view.