Publication Name	Artificial Intelligence in Medical Imaging
Manuscript ID	106928
Country	China

Category	Computer Science, Artificial Intelligence
Manuscript Type	Minireviews
Article Title	Application of artificial intelligence-assisted confocal laser endomicroscopy in gastrointestinal imaging analysis
Manuscript Source	Invited Manuscript
All Author List	Yu-Shun Liu, Ze-Hua Shi, Yan-Rui Jin, Cui-Ping Yang and Cheng-Liang Liu
Funding Agency and Grant Number	Funding Agency Grant Number Sponsored by the Interdisciplinary Program of Shanghai Jiao Tong University (project number YG2024LC01) YG2024LC01 National Natural Science Foundation of China (No. 62406190) 62406190
Corresponding Author	Cui-Ping Yang, Department of Gastroenterology, Ruijin Hospital,Shanghai Jiaotong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China. yangcuipingsgh@163.com
Key Words	Confocal laser endomicroscopy; Artificial intelligence; Gastrointestinal diseases; Medical image analysis; Early diagnosis
Core Tip	Confocal laser endomicroscopy (CLE) offers real-time imaging with cellular-level resolution and plays an important role in the early diagnosis of gastrointestinal (GI) diseases. However, its full clinical potential is often hindered by the subjectivity of manual interpretation and limitations in diagnostic efficiency. The rapid advancements in deep learning for medical image analysis have enabled the detection of subtle imaging changes that are easily missed by traditional methods. Through multidimensional feature analysis, these technologies can intelligently predict lesion malignancy, providing objective and efficient support for clinical decision-making. This review systematically presents the practical applications of artificial intelligence assisted CLE in the detection and diagnosis of GI diseases and discusses its future prospects in advancing precision medicine.
Citation	Liu YS, Shi ZH, Jin YR, Yang CP, Liu CL. Application of artificial intelligence-assisted confocal laser endomicroscopy in gastrointestinal imaging analysis. Artif Intell Med Imaging 2025; In press

Received	2025-03-24 05:56
Peer-Review Started	2025-03-24 05:56
To Make the First Decision
Return for Revision	2025-03-30 08:57
Revised	2025-04-08 02:08
Second Decision	2025-04-27 02:43
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2025-04-27 09:29
Articles in Press	2025-04-27 09:29
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2025-05-20 07:34

ISSN	2644-3260 (online)
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