Early Detection of Pancreatic Cancer: Applying Artificial Intelligence to Electronic Health Records.
Early Detection of Pancreatic Cancer: Applying Artificial Intelligence to Electronic Health Records.
复制标题
DOI：
10.1097/mpa.0000000000001882
复制
发表时间：
2021-08-01
期刊：
影响因子：
2.9
通讯作者：
Go VLW
中科院分区：
文献类型：
--
作者：
Kenner BJ;Abrams ND;Chari ST;Field BF;Goldberg AE;Hoos WA;Klimstra DS;Rothschild LJ;Srivastava S;Young MR;Go VLW
人工智能（AI）应用于电子健康记录（EHR）的临床数据以改善胰腺癌和其他癌症的早期检测的潜力仍有待探索。肯纳家族研究基金会与美国国家癌症研究所癌症生物标志物研究小组合作，于2021年3月举办了题为“胰腺癌的早期检测：利用电子健康记录（EHR）的机遇和挑战”的研讨会。研讨会包括一组精选的小组成员，他们在胰腺癌，EHR数据挖掘和基于AI的建模方面具有专业知识。这篇综述文章反映了研讨会的结果，并评估了基于AI的数据提取和建模应用于EHR的可行性。它强调了数据共享网络和通用数据模型在改善电子健康记录数据的二次使用方面日益重要的作用。目前使用EHR数据进行基于AI的建模以增强胰腺癌的早期检测的努力显示出了希望。确定了具体的挑战（生物学、有限的数据、标准、兼容性、法律的、质量、人工智能鸿沟、激励措施），总结了缓解策略，并确定了下一步措施。
The potential of artificial intelligence (AI) applied to clinical data from electronic health records (EHRs) to improve early detection for pancreatic and other cancers remains underexplored. The Kenner Family Research Fund, in collaboration with the Cancer Biomarker Research Group at the National Cancer Institute, organized the workshop entitled: “Early Detection of Pancreatic Cancer: Opportunities and Challenges in Utilizing Electronic Health Records (EHR)” in March 2021. The workshop included a select group of panelists with expertise in pancreatic cancer, EHR data mining, and AI-based modeling. This review article reflects the findings from the workshop and assesses the feasibility of AI-based data extraction and modeling applied to EHRs. It highlights the increasing role of data sharing networks and common data models in improving the secondary use of EHR data. Current efforts using EHR data for AI-based modeling to enhance early detection of pancreatic cancer show promise. Specific challenges (biology, limited data, standards, compatibility, legal, quality, AI chasm, incentives) are identified, with mitigation strategies summarized and next steps identified.