Artificial Intelligence Applications in Gastric Cancer Surgery: Bridging Early Diagnosis and Responsible Precision Medicine

<b>Background</b>: Artificial intelligence is emerging as a promising tool in surgical oncology, with growing evidence suggesting potential applications in diagnostic support, intraoperative guidance, and perioperative risk assessment. In gastric cancer surgery, emerging applications range from AI-assisted endoscopic detection to data-driven perioperative risk prediction, while some technological developments, particularly in robotic autonomy, derive from broader surgical or experimental models that may inform future gastric procedures. <b>Methods</b>: A narrative review was conducted following established methodological standards, including the Scale for the Assessment of Narrative Review Articles (SANRA) and the Search-Appraisal-Synthesis-Analysis (SALSA) framework. English-language studies indexed in PubMed, Scopus, Embase, and Web of Science up to October 2025 were included. Evidence was synthesized thematically across five domains: AI-assisted anatomical recognition and lymphadenectomy support, autonomous robotic systems, early cancer detection, perioperative predictive and frailty models, and ethical and regulatory considerations. <b>Results</b>: AI-based computer vision and deep learning algorithms have demonstrated promising capabilities for real-time anatomical recognition, surgical phase classification, and intraoperative guidance, although evidence of direct patient-level benefit remains limited. In diagnostic settings, AI-assisted endoscopy and Raman spectroscopy have been shown to improve early lesion detection and reduce dependence on operator experience. Predictive models, including MySurgeryRisk and AI-driven frailty assessments, may support individualized prehabilitation planning and perioperative risk stratification. Persistent limitations include small and heterogeneous datasets, insufficient external validation, and unresolved concerns related to data privacy, algorithmic interpretability, and medico-legal responsibility. <b>Conclusions</b>: Artificial intelligence is progressively emerging as a promising tool in gastric cancer surgery, integrating automation, advanced analytics, and human clinical reasoning. Its safe and ethical adoption requires robust validation, transparent governance, and continuous surgeon oversight. When developed within human-centered and ethically grounded frameworks, AI can augment, rather than replace, surgical expertise, potentially advancing precision, safety, and equity in oncologic care.

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Publication Details

Journal
Journal of Clinical Medicine
Published
2026-03-13
DOI
https://doi.org/10.3390/jcm15062208
Primary Topic
Gastric Cancer Management and Outcomes
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence Applications in Gastric Cancer Surgery: Bridging Early Diagnosis and Responsible Precision Medicine

Aleksandar Karamarković, Miljana Vladimirov, Rodolfo J. Oviedo, Francesco Paolo Prete et al.
Journal of Clinical Medicine
Gastric Cancer Management and Outcomes
article

Artificial Intelligence Applications in Gastric Cancer Surgery: Bridging Early Diagnosis and Responsible Precision Medicine

Aleksandar Karamarković, Miljana Vladimirov, Rodolfo J. Oviedo, Francesco Paolo Prete, Natale Calomino, Yogesh K. Vashist, Sergii Girnyi, Alberto Brolese, Borko Jovanovic, Adel Abou-Mrad, Francesco Antonio Ciarleglio, Tomasz Cwalinski, Aman Goyal, Kebebe Bekele Gonfa, Valentin Calu, Ruslan Duka, Augustinas Baušys, Adolfo Pérez Bonet, Silvia Malerba, Luigi Marano, Audrius Dulskas, M. Testini, Zilvinas Dambrauskas, Abdi Tesemma Demmo, Vikas Jain, Jaroslaw Skokowski, Karol Polom, Robert Molchanov
article en

Abstract

<b>Background</b>: Artificial intelligence is emerging as a promising tool in surgical oncology, with growing evidence suggesting potential applications in diagnostic support, intraoperative guidance, and perioperative risk assessment. In gastric cancer surgery, emerging applications range from AI-assisted endoscopic detection to data-driven perioperative risk prediction, while some technological developments, particularly in robotic autonomy, derive from broader surgical or experimental models that may inform future gastric procedures. <b>Methods</b>: A narrative review was conducted following established methodological standards, including the Scale for the Assessment of Narrative Review Articles (SANRA) and the Search-Appraisal-Synthesis-Analysis (SALSA) framework. English-language studies indexed in PubMed, Scopus, Embase, and Web of Science up to October 2025 were included. Evidence was synthesized thematically across five domains: AI-assisted anatomical recognition and lymphadenectomy support, autonomous robotic systems, early cancer detection, perioperative predictive and frailty models, and ethical and regulatory considerations. <b>Results</b>: AI-based computer vision and deep learning algorithms have demonstrated promising capabilities for real-time anatomical recognition, surgical phase classification, and intraoperative guidance, although evidence of direct patient-level benefit remains limited. In diagnostic settings, AI-assisted endoscopy and Raman spectroscopy have been shown to improve early lesion detection and reduce dependence on operator experience. Predictive models, including MySurgeryRisk and AI-driven frailty assessments, may support individualized prehabilitation planning and perioperative risk stratification. Persistent limitations include small and heterogeneous datasets, insufficient external validation, and unresolved concerns related to data privacy, algorithmic interpretability, and medico-legal responsibility. <b>Conclusions</b>: Artificial intelligence is progressively emerging as a promising tool in gastric cancer surgery, integrating automation, advanced analytics, and human clinical reasoning. Its safe and ethical adoption requires robust validation, transparent governance, and continuous surgeon oversight. When developed within human-centered and ethically grounded frameworks, AI can augment, rather than replace, surgical expertise, potentially advancing precision, safety, and equity in oncologic care.

Journal of Clinical MedicineVol. 15(6)
University of Siena (IT), Madda Walabu University (ET), Mahatma Gandhi Medical College and Research Institute (IN), Lithuanian University of Health Sciences (LT), University of Nis (RS), Carol Davila University of Medicine and Pharmacy (RO), Vilnius University (LT), Adesh University (IN), University of Belgrade (RS), Azienda Ospedaliera di Perugia (IT), Kliničko Bolnički Centar Zvezdara (RS), Społeczna Akademia Nauk (PL), Provincia Autonoma di Trento (IT), Hospital La Inmaculada (ES), Klinikum Lippe (DE), HCG Cancer Centre (IN), Centre hospitalier universitaire d'Orléans (FR), National Cancer Institute (LT), Dietrich Bonhoeffer Klinikum (DE), Prywatna Wyższa Szkoła Nauk Społecznych, Komputerowych i Medycznych (PL), Lehmann Eye Center (US), University of Houston (US), Institute of Medical Sciences (IN), University of Bari Aldo Moro (IT), Dnipro State Medical University (UA)
Openalex Percentile: Top 23%
Gastric Cancer Management and Outcomes
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