Work

Circulating Biomarkers with Artificial Intelligence for Clinical Risk Assessment and Therapeutic Monitoring: Evidence, Limitations, and Translation

Year: 2026

Type: review

Abstract: Circulating biomarkers, particularly cell-free DNA (cfDNA), are transforming contemporary medicine through their capacity to provide dynamic, minimally invasive assessments of disease dynamics. Their clinical utility has broadened substantially to include oncology, cardiovascular conditions, transplant monitoring, infectious diseases, and persistent inflammatory disorders. Nevertheless, the increasing complexity and volume of biomarker-related data pose substantial challenges, necessitating the integration of artificial intelligence (AI) and machine learning methodologies for improved data interpretation, risk assessment, and clinical decision-making. This review presents a thorough examination of recent progress in the integration of circulating biomarkers with AI within therapeutic contexts and clinical risk management. It outlines the translational trajectory from molecular signatures to precision medicine, addresses present constraints, and explores prospective developments. The objective of this review is to serve as a systematic resource for both clinical practice and research, thereby promoting the evolution of personalized medicine through innovative, biomarker-driven strategies supported by AI.

Source: Therapeutics and Clinical Risk Management

DOI: 10.2147/tcrm.s612081

Authors: Wenyuan Wei, Rui Zhang, Zhiying Zhang

Institution: Inner Mongolia Medical University

Language: English

Topic: Cancer Genomics and Diagnostics

Subfield: Cancer Research

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,836