Publication Name	World Journal of Clinical Cases
Manuscript ID	118581
Country	United States

Category	Medicine, General & Internal
Manuscript Type	Minireviews
Article Title	Artificial intelligence advancement in addressing cough
Manuscript Source	Invited Manuscript
All Author List	Rubi Thapa, Vivek Paudyal, Munish Sharma, Iqbal Ratnani and Salim Surani
Funding Agency and Grant Number
Corresponding Author	Salim Surani, FACP, FCCP, MD, Professor, Department of Medicine, University of Houston, 4302 University Drive, Houston, TX 77004, United States. srsurani@hotmail.com
Key Words	Acoustics; Artificial intelligence; Cough; Cough sound analysis; Deep learning; Machine learning
Core Tip	Evaluating cough for pulmonary conditions relies substantially on acoustic measurement, yet existing quantification tools remain suboptimal. Integrating artificial intelligence (AI), particularly machine learning and deep learning, offers a promising pathway for both therapeutic and preventive applications in cough medicine. Current implementations remain confined to weak AI’s predefined roles, while advances in artificial general intelligence hold the potential to overcome these adaptability constraints. Moreover, harnessing current potential requires resolving key technical, ethical, and legal issues by integrating explainable AI, multimodal hybrid approaches, and robust accountability measures within human-centered frameworks.
Citation	Thapa R, Paudyal V, Sharma M, Ratnani I, Surani S. Artificial intelligence advancement in addressing cough. World J Clin Cases 2026; In press

Received	2026-01-06 07:15
Peer-Review Started	2026-01-06 07:15
First Decision by Editorial Office Director	2026-01-14 07:57
Return for Revision	2026-01-14 07:57
Revised	2026-01-22 15:38
Publication Fee Transferred
Second Decision by Editor	2026-02-06 02:48
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-02-06 06:39
Articles in Press	2026-02-06 06:39
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	2307-8960 (online)
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: http://creativecommons.org/licenses/by-nc/4.0/
Copyright	©The Author(s) 2026. Published by Baishideng Publishing Group Inc. All rights reserved.
Permissions	For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher	Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website	http://www.wjgnet.com