TrajOnco: a multi-agent framework for temporal reasoning over longitudinal EHR for multi-cancer early detection

Accurate estimation of cancer risk from longitudinal electronic health records (EHRs) could support earlier detection and improved care, but modeling such complex patient trajectories remains challenging. We present TrajOnco, a training-free, multi-agent large language model (LLM) framework designed for scalable multi-cancer early detection. Using a chain-of-agents architecture with long-term memory, TrajOnco performs temporal reasoning over sequential clinical events to generate patient-level s

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ethics.ai (12 April 2026), “TrajOnco: a multi-agent framework for temporal reasoning over longitudinal EHR for multi-cancer early detection,” evidence record 6018, https://ethics.ai/record/6018 (originally published by arXiv).

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