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Recurrent Longitudinal Memory (ReLMem), a framework that learns to maintain fixed-capacity patient memory for efficient downstream prediction with a frozen LLM, is introduced and a multi-granularity optimization strategy to preserve task-relevant information throughout recurrent updates and support downstream predictio...
CDEG, a graph-based framework that learns reusable decision-critical evidence from historical diagnostic trajectories, is introduced, demonstrating that reliable long-horizon diagnosis requires moving beyond trajectory-level experience reuse toward evidence-level learning of the factors that truly shape clinical decisi...
The Medical Information Response Audit (MIRA), a bilingual, controlled benchmark that assesses whether LLMs provide comparable medical information across user-side language, register, and health literacy signals, is introduced.
DentVLM is a dental vision-language model developed to support dental diagnosis across seven oral imaging modalities and 36 tasks that surpasses junior readers, matches intermediate general practitioners and approaches senior specialists, and reduces diagnostic time by 15.0-37.0% in collaborative clinical workflows.
DentAgent is introduced, an evidence-centric multi-agent framework, in which the Orchestrator coordinate five specialized agents spanning various modalities, which supports its value for broadly applicable and traceable multimodal dental reasoning, and highlights its potential as a technical foundation for population o...
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