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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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GPSai:一款经过临床验证的AI工具,用于在常规瘤分析过程中预测起源组织.

Hassan Ghani1, Anthony Helmstetter1, Jennifer R Ribeiro1

  • 1Caris Life Sciences, Irving, Texas.

Cancer research communications
|July 31, 2025
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概括

一个人工智能 (AI) 工具,基因组概率得分AI (GPSaiTM),准确地识别出癌症组织的起源,有助于诊断未知的原发性癌症 (CUP) 并改善治疗决策.

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科学领域:

  • 在瘤学瘤学.
  • 生物信息学是一种生物信息学.
  • 人工智能在医学中的应用

背景情况:

  • 癌症的一个子集,存在不清楚或不正确的原发性组织病理学诊断,在诊断和治疗方面构成挑战.
  • 未知初级癌症 (CUP) 是一个重大的诊断困境,影响患者管理和治疗策略.

研究的目的:

  • 开发和验证一个人工智能工具,基因组概率得分人工智能 (GPSaiTM),用于预测CUP中的瘤组织起源,并识别潜在的误诊.
  • 评估将GPSai整合到常规分子测试中的临床影响,以提高诊断准确性和指导治疗.

主要方法:

  • GPSai模型是从超过20万个病例的整个外体和转录组数据上训练的.
  • 在超过97,000个案例中进行了回顾性和前性验证.
  • 通过8个月的活体测试和医生调查来评估临床效用.

主要成果:

  • 在非CUP病例中,GPSai显示95.0%的准确性,在84.0%的CUP病例中确定瘤起源.
  • 该工具在0.88%的分析病例中导致了诊断变化,这些变化得到了正交证据的支持.
  • 在86.1%的受影响患者中,诊断的改变促使了针对性治疗资格的变化.

结论:

  • GPSai准确地识别出瘤组织的起源,帮助诊断CUP和模两可的瘤.
  • 人工智能工具通过提高诊断准确性和指导随后的治疗决策,有可能产生临床影响.
  • 将GPSai集成到常规分子测试中可以提高诊断精度并优化患者治疗策略.