Early Detection of Pancreatic Cancer

Pancreas - Tập 50 Số 7 - Trang 916-922 - 2021
Barbara Kenner1, Natalie Abrams2, Suresh T. Chari3, Bruce F. Field1, Ann Goldberg1, William Hoos4, David S. Klimstra5, Laura J. Rothschild1, Sudhir Srivastava2, Matthew R. Young2, Vay Liang W. Go6
1Kenner Family Research Fund, New York, NY
2Division of Cancer Prevention, National Cancer Institute, Bethesda, MD
3Department of Gastroenterology, Hepatology, and Nutrition, The University of Texas MD Anderson Cancer Center, Houston, TX
4Canopy Cancer Collective, Chapel Hill, NC
5Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY
6UCLA Center for Excellence in Pancreatic Diseases, University of California, Los Angeles, Los Angeles, CA.

Tóm tắt

Abstract 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.

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Pancreas

Tập 50 Số 7

916-922

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