Automated Extraction of Patient-Centered Outcomes After Breast Cancer Treatment: An Open-Source Large Language Model-Based Toolkit.

Journal: JCO clinical cancer informatics
Published Date: Aug 1, 2024

Abstract

PURPOSE: Patient-centered outcomes (PCOs) are pivotal in cancer treatment, as they directly reflect patients' quality of life. Although multiple studies suggest that factors affecting breast cancer-related morbidity and survival are influenced by treatment side effects and adherence to long-term treatment, such data are generally only available on a smaller scale or from a single center. The primary challenge with collecting these data is that the outcomes are captured as free text in clinical narratives written by clinicians.

Authors

  • Man Luo
    School of Art and Design, Shanghai University of Engineering Science, Shanghai, 201620, PR. China.
  • Shubham Trivedi
    Department of Radiology, Mayo Clinic, Phoenix, Arizona, USA.
  • Allison W Kurian
    Department of Medicine, Stanford University School of Medicine, Stanford, CA.
  • Kevin Ward
  • Theresa H M Keegan
    Department of Biomedical Data Science, Radiology, and Medicine, Stanford University School of Medicine, Palo Alto, CA.
  • Daniel Rubin
    Department of Radiology, Stanford University, Stanford, CA, USA.
  • Imon Banerjee
    Mayo Clinic, Department of Radiology, Scottsdale, AZ, USA.

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