AI-guided wound closure: complementing surgical judgment

Artificial intelligence (AI) is redefining the precision of surgical wound closure through innovations in deep learning, computer vision, and robotic control. These technologies enable automated wound assessment, trajectory planning, and suturing assistance, with applications emerging across the United States, the United Kingdom, Japan, and India. Yet, the art of closure balancing tension, perfusion, and tissue integrity remains a fundamentally human skill. This work additionally highlights the current gap between theoretical AI capabilities and clinical validation, clarifies tissue-specific and interpretability challenges, and outlines concrete research pathways, including prospective trials, interpretable AI, and multimodal fusion systems. This letter discusses the clinical and technical aspects of AI-guided wound closure, emphasizing the importance of maintaining surgeon oversight. It argues that AI can enhance, but not supplant, human judgment, aligning with international guidelines on transparency and safety in AI deployment. Widespread clinical adoption will require rigorous validation, equitable access, and adherence to frameworks such as the TITAN Guidelines to ensure ethical and effective integration into surgical practice.

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Publication Details

Journal
Annals of Medicine and Surgery
Published
2026-01-22
DOI
https://doi.org/10.1097/ms9.0000000000004724
Primary Topic
Surgical Sutures and Adhesives
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-guided wound closure: complementing surgical judgment

Muhammad Salman Zaib, Hasiba Karimi, Muhammad Khizar, Hasibullah Aminpoor et al.
Annals of Medicine and Surgery
Surgical Sutures and Adhesives
article

AI-guided wound closure: complementing surgical judgment

Muhammad Salman Zaib, Hasiba Karimi, Muhammad Khizar, Hasibullah Aminpoor, Nukhbat-Ul Nisa
article en

Abstract

Artificial intelligence (AI) is redefining the precision of surgical wound closure through innovations in deep learning, computer vision, and robotic control. These technologies enable automated wound assessment, trajectory planning, and suturing assistance, with applications emerging across the United States, the United Kingdom, Japan, and India. Yet, the art of closure balancing tension, perfusion, and tissue integrity remains a fundamentally human skill. This work additionally highlights the current gap between theoretical AI capabilities and clinical validation, clarifies tissue-specific and interpretability challenges, and outlines concrete research pathways, including prospective trials, interpretable AI, and multimodal fusion systems. This letter discusses the clinical and technical aspects of AI-guided wound closure, emphasizing the importance of maintaining surgeon oversight. It argues that AI can enhance, but not supplant, human judgment, aligning with international guidelines on transparency and safety in AI deployment. Widespread clinical adoption will require rigorous validation, equitable access, and adherence to frameworks such as the TITAN Guidelines to ensure ethical and effective integration into surgical practice.

Annals of Medicine and SurgeryVol. 88(3)
Kabul University (AF), Bezmiâlem Vakıf Üniversitesi (TR), Kabul University of Medical Sciences Abu Ali Ibn Sina (AF), Georgian American University (GE), Shaikh Zayed Postgraduate Medical Institute (PK)
Openalex Percentile: Top 81%
Surgical Sutures and Adhesives
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