Early Detection of Pancreatic Cancer: Applying Artificial Intelligence to Electronic Health Records.

Journal: Pancreas
PMID: 34629446

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.

Authors

  • Barbara J Kenner
    From the Kenner Family Research Fund, New York, NY.
  • Natalie D Abrams
    Division of Cancer Prevention, National Cancer Institute, Bethesda, MD.
  • Suresh T Chari
    Department of Gastroenterology, Hepatology and Nutrition, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA.
  • Bruce F Field
    From the Kenner Family Research Fund, New York, NY.
  • Ann E Goldberg
    From the Kenner Family Research Fund, New York, NY.
  • William A Hoos
    Canopy Cancer Collective, Chapel Hill, NC.
  • David S Klimstra
    Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Laura J Rothschild
    From the Kenner Family Research Fund, New York, NY.
  • Sudhir Srivastava
    Department of Biochemistry and Molecular Medicine, George Washington University, Washington, DC 20037, USA, Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA, Center for Bioinformatics and Information Technology, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20892-9760, USA, NASA Jet Propulsion Laboratory, Pasadena, CA, USA, Division of Cancer Prevention, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20892-9760, USA, Wellcome Trust Sanger Institute, Cambridge, UK and McCormick Genomic and Proteomic Center, George Washington University, Washington, DC 20037, USA.
  • Matthew R Young
    From the Cancer Biomarker Research Group, Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Rockville, MD.
  • Vay Liang W Go
    UCLA Center for Excellence in Pancreatic Diseases, University of California, Los Angeles, Los Angeles, CA.

Keywords

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