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This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (3558) Clinical Information and Decision Making (2138) New Methods (1199) mHealth in a Clinical Setting (800) Imaging Informatics (350) Artificial Intelligence (2441)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69940, first published .
Implementation of Fully Automated AI-Integrated System for Body Composition Assessment on Computed Tomography for Opportunistic Sarcopenia Screening: Multicenter Prospective Study

Implementation of Fully Automated AI-Integrated System for Body Composition Assessment on Computed Tomography for Opportunistic Sarcopenia Screening: Multicenter Prospective Study

Implementation of Fully Automated AI-Integrated System for Body Composition Assessment on Computed Tomography for Opportunistic Sarcopenia Screening: Multicenter Prospective Study

Authors of this article:

Bushra Urooj1, 2 Author Orcid Image ;   Yousun Ko1, 2 Author Orcid Image ;   Seongwon Na1, 2 Author Orcid Image ;   In-One Kim3 Author Orcid Image ;   Eun-Hee Lee3 Author Orcid Image ;   Seon Cho3 Author Orcid Image ;   Heeryeol Jeong4 Author Orcid Image ;   Seungwoo Khang4 Author Orcid Image ;   Jeongjin Lee4 Author Orcid Image ;   Kyung Won Kim1, 2 Author Orcid Image
Article Authors Cited by (8) Tweetations Metrics

Journals

  1. Park H, Kim H, Yoo J. AI-Enhanced Lower Extremity X-Ray Segmentation: A Promising Tool for Sarcopenia Diagnosis. Healthcare 2025;13(19):2488 View
  2. Kolenda P, Mardas M, Radomyski P, Trojanowski M, Litwiniuk M, Warchoł W, Stelmach-Mardas M. Body Composition and Survival in Locally Advanced Rectal Cancer Patients Treated with Neoadjuvant Radiochemotherapy. Nutrients 2025;17(20):3309 View
  3. Yu H. Sarcopenia in Interventional Radiology: An Opportunistic Imaging Biomarker for Patient Outcomes and Procedural Planning. Muscles 2025;4(4):55 View
  4. Ferrera-Alayón L, Palmas-Candia F, Salas-Salas B, González-Martín J, Diaz-Saavedra R, Ramos-Ortiz A, Lara P, Lloret Sáez-Bravo M. Development and Internal Evaluation of AI-Assisted Cervical Muscle-Based Scores (FUNC-RISK) in Head and Neck Cancer: A Pilot Study. Cancers 2025;17(24):3968 View
  5. Tamir S, Behar H, Tal R, Jasper R, Armoni M, Aloni H, Orad R, Voet H, Atar E, Grubstein A, Stemmer S, Markel G. CT Body Composition Changes Predict Survival in Immunotherapy-Treated Cancer Patients: A Retrospective Cohort Study. Cancers 2026;18(2):341 View
  6. Makras P, Chatzellis E, Gravvanis C, Kanti G, Yavropoulou M, Papadimitropoulos K, Kyriakopoulos N, Tekedis C, Mparmparousi V, Liakopoulos I, Matsaridis D, Skoulikaris E, Varela M, Athanasiou H, Koropouli S, Gidarakos N. Artificial intelligence vs human opportunistic detection of vertebral fractures in routine CT scans: results of a pilot study. Hormones 2026 View
  7. Luo Y, Bu D, Wu Y, Zhao Y. Artificial Intelligence in Medical Informatics: From Algorithms to Clinical Practice—A Survey. Journal of Computer Science and Technology 2026;41(1):447 View
  8. Moyal J, Rehany B. Radiological assessment of body composition changes and complications in an era of incretin-based therapies: A narrative review. University of Toronto Medical Journal 2026;103(2) View