Identifying abdominal aortic aneurysm size and presence using Natural Language Processing of radiology reports: a systematic review and meta-analysis.

Journal: Abdominal radiology (New York)
Published Date: Jan 30, 2025

Abstract

BACKGROUND AND AIM: Prior investigations of the natural history of abdominal aortic aneurysms (AAAs) have been constrained by small sample sizes or uneven assessments of aggregated data. Natural language processing (NLP) can significantly enhance the investigation and treatment of patients with AAAs by swiftly and effectively collecting imaging data from health records. This meta-analysis aimed to evaluate the efficacy of NLP techniques in reliably identifying the existence or absence of AAAs and measuring the maximal abdominal aortic diameter in extensive datasets of radiology study reports.

Authors

  • Seyed Mohammad Sajjadi
    Mashhad University of Medical Sciences, Mashhad, Islamic Republic of Iran.
  • Alisa Mohebbi
    Students' Scientific Research Center Tehran University of Medical Sciences Tehran Iran.
  • Amirhossein Ehsani
    Iran University of Medical Sciences, Tehran, Islamic Republic of Iran.
  • Amir Marashi
    School of Medical Science, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.
  • Aida Azhdarimoghaddam
    Student Research Committee, School of Medicine, Zahedan University of Medical Sciences, Zahedan, Iran.
  • Shaghayegh Karami
    Students' Scientific Research Center (SSRC), Tehran University of Medical Sciences, Tehran, Iran.
  • Mohammad Amin Karimi
    Shahid Beheshti University of Medical Sciences, Tehran, Islamic Republic of Iran.
  • Mahsa Sadeghi
    Department of Endodontics, Shahed University, Tehran, Iran.
  • Kiana Firoozi
    Gonabad University of Medical Sciences, Gonābād, Islamic Republic of Iran.
  • Amir Mohammad Zamani
    Ahvaz Jundishapur University of Medical Sciences, Ahvāz, Islamic Republic of Iran.
  • Amirhossein Rigi
    Department of Radiology, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Melika Nayebagha
    Shahid Beheshti University of Medical Sciences, Tehran, Islamic Republic of Iran.
  • Mahsa Asadi Anar
    Student Research Committee, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Pooya Eini
    Toxicological Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  • Sadaf Salehi
    Student Research Committee, Iran University of Medical Sciences, Tehran, Iran.
  • Mahsa Rostami Ghezeljeh
    Kerman University of Medical Sciences, Kerman, Islamic Republic of Iran.

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