人工智能支持知情决策 (INSIDE) 改善瘤学文献分析
Arnulf Stenzl1, Andrew J Armstrong2, Andrea Sboner3
1Department of Urology, University Hospital Tübingen, Tübingen, Germany.
European urology focus
|June 14, 2024
概括
人工智能 (AI) 工具INSIDE PC通过分析医学文献来帮助确定最佳的前列腺癌治疗序列. INSIDE PC展示了与PubMed相比的竞争性表现,增强了高级前列腺癌治疗的临床决策.
科学领域:
- 人工智能在医学中的应用
- 计算生物学和生物信息学
- 瘤学和癌症研究研究.
背景情况:
- 在前列腺癌 (PC) 中优化治疗序列是复杂的,可以从AI驱动的医学文献分析中受益.
- 现有的文献搜索工具可能无法有效地为PC中复杂的治疗决策提供相关信息.
研究的目的:
- 验证INSIDE PC平台用于查询前列腺癌治疗测序文献.
- 建立评估基于人工智能的临床支持工具的方法.
- 评估与PubMed相比,INSIDE PC在检索相关PC治疗信息方面的表现.
主要方法:
- INSIDE PC是使用PubMed双向编码器表示从变压器进行语义文献分析而开发的.
- 用数据分析对出版物进行了排名和可视化,以确定其相关性.
- 专家评估使用正常化折扣累积增益 (nDCG) 评分,对比了INSIDE PC和PubMed对特定PC治疗顺序问题的输出.
主要成果:
- 在新型荷尔蒙疗法 (NHT) 的相关性方面,INSIDE PC的表现优于PubMed,其次是NHT (问题1) 和NHT或PARPi,其次是177Lu-PSMA-617 (问题3).
- 在INSIDE PC和PubMed之间,NHT的性能与多 (ADP-ribose) 聚合酶抑制剂 (PARPi) 相似 (问题2).
- 在特定场景中,INSIDE PC 展示了在前5,前10和前20个获取的出版物中优越的排名和相关性.
结论:
- INSIDE PC有效地帮助临床医生浏览前列腺癌治疗序列的文献.
- 该研究建立了评估AI文献提取工具的标准.
- INSIDE PC表现出与PubMed竞争的表现,并支持在先进的PC治疗中共享决策.
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