Generative AI–Enabled Imaging Substitution for Equitable Preoperative Decision-Making in Rectal Cancer Care (Extended Abstract)

Authors

  • Chang Li Department of Biosciences and Bioinformatics & Suzhou Municipal Key Lab of AI4Health, School of Science, Xi’an Jiaotong-Liverpool University Department of Mathematical Sciences, School of Physical Sciences, University of Liverpool
  • Xiang Zhao Qilu Hospital of Shandong University
  • Jia Meng Department of Biosciences and Bioinformatics & Suzhou Municipal Key Lab of AI4Health, School of Science, Xi’an Jiaotong-Liverpool University
  • John Moraros Department of Biosciences and Bioinformatics & Suzhou Municipal Key Lab of AI4Health, School of Science, Xi’an Jiaotong-Liverpool University
  • Shuihua Wang Department of Biosciences and Bioinformatics & Suzhou Municipal Key Lab of AI4Health, School of Science, Xi’an Jiaotong-Liverpool University

DOI:

https://doi.org/10.1609/aaaiss.v9i1.42929

Abstract

This extended abstract presents a generative AI-enabled framework for rectal cancer that supports mesenteric fascia (MRF) invasion assessment under CT-only workflows, aiming to improve diagnostic equity, decision quality, and healthcare resource efficiency in real-world settings.
2026 AAAI Summer Symposium Proceedings Cover

Downloads

Published

2026-06-23

How to Cite

Li, C., Zhao, X., Meng, J., Moraros, J., & Wang, S. (2026). Generative AI–Enabled Imaging Substitution for Equitable Preoperative Decision-Making in Rectal Cancer Care (Extended Abstract). Proceedings of the AAAI Symposium Series, 9(1), 217–218. https://doi.org/10.1609/aaaiss.v9i1.42929

Issue

Vol. 9 No. 1: Proceedings of the 2026 AAAI Summer Symposium Series

Section

AI in Business: Intelligent Transformation and Management (Extended Abstracts)