BioInsight: Multi-Agent Orchestration for Interactive Biomedical Knowledge Discovery
📰 ArXiv cs.AI
arXiv:2606.20997v1 Announce Type: new Abstract: Biomedical researchers increasingly use AI-generated analyses and reports to interpret protein-level signals, but static outputs are often insufficient for research decision-making, where users need to inspect evidence, assess uncertainty, compare mechanisms, and refine hypotheses. We present \textsc{BioInsight}, a multi-agent system that moves from static biomedical report generation to interactive evidence-centered interactive interface generatio
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Title: BioInsight: Multi-Agent Orchestration for Interactive Biomedical Knowledge Discovery
Abstract:
arXiv:2606.20997v1 Announce Type: new Abstract: Biomedical researchers increasingly use AI-generated analyses and reports to interpret protein-level signals, but static outputs are often insufficient for research decision-making, where users need to inspect evidence, assess uncertainty, compare mechanisms, and refine hypotheses. We present \textsc{BioInsight}, a multi-agent system that moves from static biomedical report generation to interactive evidence-centered interactive interface generatio
Abstract:
arXiv:2606.20997v1 Announce Type: new Abstract: Biomedical researchers increasingly use AI-generated analyses and reports to interpret protein-level signals, but static outputs are often insufficient for research decision-making, where users need to inspect evidence, assess uncertainty, compare mechanisms, and refine hypotheses. We present \textsc{BioInsight}, a multi-agent system that moves from static biomedical report generation to interactive evidence-centered interactive interface generatio
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