Advancing Clinical Genomic Analysis with a Skill-Centred Agent· 用技能中心代理推进临床基因组分析
Clinical genomic analysis requires experts to integrate evolving guidelines, databases, and computational evidence. As sequencing has become increasingly accessible, this complex and labor-intensive process has become a major bottleneck to the timely use of genomic information in clinical decision-making. To fill this gap, we developed ClinGeX, a large-language-model agent that composes 105 curated executable skills through task-specific retrieval and dependency-aware orchestration. On 223 temporally held-out benchmark cases, ClinGeX achieved 71.7\% macro-averaged task-level concordance with expert reference classifications, compared with 45.7\% for the strongest comparator. In a three-condition, counterbalanced human-AI collaboration study, 45 clinical genomic professionals assessed 135 c
ClinGeX 利用大型语言模型推进临床基因组分析，提高决策效率。
- 核心方法
- ClinGeX 通过任务特定检索和依赖关系感知编排，整合 105 个精心策划的可执行技能，利用大型语言模型代理提高分析效率。
- 适合谁读
- 研究者、工程师、临床基因组专业人士
- 要解决的问题
- 解决临床基因组分析中专家资源短缺和决策效率低下的问题。
- 关键实验
- 在 223 个基准案例中，ClinGeX 达到 71.7% 的任务级一致性；进行了三条件平衡的人机协作研究，45 名临床基因组专业人士评估了 135 个案例。
- 主要贡献
- 实现了 71.7% 的任务级一致性，显著优于最强对比方法 45.7%；在人机协作研究中表现出色。
- 意义与局限
- 提高了临床基因组分析的效率和准确性，有助于快速整合基因组信息用于临床决策。局限性在于需要进一步验证和优化，以适应更多样化的临床环境。