Predicting decompression surgery by applying multimodal deep learning to patients' structured and unstructured health data.

Journal: BMC medical informatics and decision making
PMID: 36609379

Abstract

BACKGROUND: Low back pain (LBP) is a common condition made up of a variety of anatomic and clinical subtypes. Lumbar disc herniation (LDH) and lumbar spinal stenosis (LSS) are two subtypes highly associated with LBP. Patients with LDH/LSS are often started with non-surgical treatments and if those are not effective then go on to have decompression surgery. However, recommendation of surgery is complicated as the outcome may depend on the patient's health characteristics. We developed a deep learning (DL) model to predict decompression surgery for patients with LDH/LSS.

Authors

  • Chethan Jujjavarapu
    Department of Biomedical Informatics and Medical Education (C.J., V.P., T.A.C., S.D.M.), School of Medicine, University of Washington, Seattle, Washington.
  • Pradeep Suri
    Department of Rehabilitation Medicine, University of Washington, Seattle, WA, USA.
  • Vikas Pejaver
    Department of Biomedical Informatics and Medical Education and the eScience Institute, University of Washington, Seattle, Washington 98109, USA; email: vpejaver@uw.edu.
  • Janna Friedly
    Clinical Learning, Evidence and Research Center, University of Washington, 4333 Brooklyn Ave NE, Seattle, WA, 98105, USA.
  • Laura S Gold
    Clinical Learning, Evidence and Research Center, University of Washington, 4333 Brooklyn Ave NE, Seattle, WA, 98105, USA.
  • Eric Meier
    Clinical Learning, Evidence and Research Center, University of Washington, 4333 Brooklyn Ave NE, Seattle, WA, 98105, USA.
  • Trevor Cohen
    University of Washington, Seattle, WA.
  • Sean D Mooney
    Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA.
  • Patrick J Heagerty
    Department of Biostatistics, University of Washington, Seattle, WA, USA.
  • Jeffrey G Jarvik
    Comparative Effectiveness, Cost and Outcomes Research Center, University of Washington, Seattle, WA, USA. jarvikj@uw.edu.

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