Emerging Roles of Multiparametric Biodosimetry and Artificial Intelligence in Advancing Radiation Dose Assessment for Triage

Biodosimetry plays a crucial role in radiation emergency preparedness and response by enabling efficient allocation of medical resources through prioritization of individuals needing urgent care to improve survival outcomes. Because currently available biodosimetry tools vary widely in sensitivity and specificity, a single assay may not be sufficient for various exposure scenarios that differ in radiation quality (low or high LET, single or mixed beam), radiation dose, dose rate (low or high), and exposure mode (acute or chronic, whole or partial body). Complex mass-casualty incidents may require a tiered multiparametric biodosimetry (MPBD) approach to improve dose prediction accuracy and the scalability of radiation dose measurements. A tiered MPBD approach can be developed by carefully combining clinical signs and symptoms with biological and physical dosimetry assays to achieve rapid screening (24-48 h after the incident), exposure dose categorization for medical treatment (minimal exposure <1 Gy, moderate exposure 1-2 Gy, severe exposure 2-6 Gy, and lethal exposure >6 Gy), and definitive dose assessment to predict and monitor long-term health risks. This review proposes a strategic tiered MPBD approach that integrates artificial intelligence (AI)-based tools to support effective medical triage in the aftermath of small- and large-scale radiological/nuclear incidents.