Enhancing Aortic Aneurysm Surveillance: Transformer Natural Language Processing for Flagging and Measuring in Radiology Reports.

Journal: Annals of vascular surgery
PMID: 39424172

Abstract

BACKGROUND: Incidental findings of aortic aneurysms (AAs) often go unreported, and established patients are frequently lost to follow-up. Natural language processing (NLP) offers a promising solution to address these issues. While rule-based NLP methods have shown some success, recent advancements in transformer-based large language models (LLMs) remain underutilized. This study has 3 following aims: (1) to evaluate the effectiveness of our innovative transformer-based NLP pipeline regarding AA detection; (2) to detail the clinical impact by quantifying the number of patients who could benefit from such technology; and (3) to use this information to help coordinate appointments with patients, ensuring proper monitoring and management.

Authors

  • William Kartsonis
    Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA.
  • Paola Pastena
    Division of Cardiology, Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA.
  • Janos Hajagos
    Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York.
  • Kelly Hirsch
    Division of Vascular Surgery, Department of Surgery, Stony Brook University Hospital, Stony Brook, NY, USA.
  • Kevin Gilotra
    Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA.
  • Shamanth Murundi
    Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA.
  • Ashna Raiker
    Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA.
  • Chris de la Bastide
    Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA.
  • Camilo Martinez
    Department of Ophthalmology, Children's National Medical System, Washington, DC, USA.
  • Apostolos Tassiopoulos
    Division of Vascular Surgery, Department of Surgery, Stony Brook University Hospital, Stony Brook, NY, USA. Electronic address: apostolos.tassiopoulos@stonybrookmedicine.edu.

Keywords

External Resources

Popular Topics
Recent Journals