Letter to the Editor
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Oncol. Aug 24, 2025; 16(8): 109893
Published online Aug 24, 2025. doi: 10.5306/wjco.v16.i8.109893
Deep learning models for pathological classification and staging of oesophageal cancer
Himanshu Agrawal, Nikhil Gupta
Himanshu Agrawal, Department of Surgery, University College of Medical Sciences (University of Delhi), GTB Hospital, Delhi 110095, India
Nikhil Gupta, Department of Surgery, Atal Bihari Vajpayee Institute of Medical Sciences and Dr. Ram Manohar Lohia Hospital, Delhi 110001, India
Author contributions: Agrawal A and Gupta N were responsible for research conception and design, data acquisition, data analysis and interpretation, drafting of the manuscript, critical revision of the manuscript, supervision and approval of the final manuscript.
Conflict-of-interest statement: There is no conflict of interest associated with any of the senior author or other coauthors contributed their efforts in this manuscript.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Nikhil Gupta, MD, Professor, Department of Surgery, Atal Bihari Vajpayee Institute of Medical Sciences and Dr. Ram Manohar Lohia Hospital, BKS Marg, Delhi 110001, India. nikhil_ms26@yahoo.co.in
Received: May 26, 2025
Revised: June 4, 2025
Accepted: July 7, 2025
Published online: August 24, 2025
Processing time: 88 Days and 0.3 Hours
Core Tip

Core Tip: This letter highlights Wei et al’s study on the Wave-Vision Transformer (Wave-ViT), an advanced deep learning model integrating frequency-domain analysis for accurate, efficient pathological classification and staging of oesophageal cancer. Wave-ViT shows superior performance and clinical potential in early cancer detection and personalized treatment, though broader validation and explainability remain essential.