
==== Front
Ann Gastroenterol Surg
Ann Gastroenterol Surg
10.1002/(ISSN)2475-0328
AGS3
Annals of Gastroenterological Surgery
2475-0328
John Wiley and Sons Inc. Hoboken

10.1002/ags3.12827
AGS312827
AGS-2024-0170
Letter to the Editor
Letter to the Editor
Artificial intelligence‐driven surgical innovation: A catalyst for medical equity
LETTER TO THE EDITOR
Chiu Si‐Wai Vivian 1 2
Liu Chung‐Feng 3
Liao Kuang‐Ming 4 5
Chiu Chong‐Chi https://orcid.org/0000-0002-1696-2648
6 7 8 chiuchongchi@gmail.com

1 Center for Computational Molecular Biology Brown University Providence Rhode Island USA
2 Department of Economics Brown University Providence Rhode Island USA
3 Department of Medical Research Chi Mei Medical Center Tainan Taiwan
4 Department of Internal Medicine Chi Mei Medical Center Chiali Taiwan
5 Department of Nursing Min‐Hwei Junior College of Health Care Management Tainan Taiwan
6 Department of General Surgery, E‐Da Cancer Hospital I‐Shou University Kaohsiung Taiwan
7 School of Medicine, College of Medicine I‐Shou University Kaohsiung Taiwan
8 Department of Medical Education and Research, E‐Da Cancer Hospital I‐Shou University Kaohsiung Taiwan
* Correspondence
Chong‐Chi Chiu, Department of General Surgery, E‐Da Cancer Hospital, I‐Shou University, No. 21, Yi‐Da Road, Jiao‐Su Village, Yan‐Chao District, Kaohsiung City 824, Taiwan.
Email: chiuchongchi@gmail.com

27 5 2024
9 2024
8 5 10.1002/ags3.v8.5 952953
07 5 2024
12 5 2024
© 2024 The Author(s). Annals of Gastroenterological Surgery published by John Wiley & Sons Australia, Ltd on behalf of The Japanese Society of Gastroenterological Surgery.
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

source-schema-version-number2.0
cover-dateSeptember 2024
details-of-publishers-convertorConverter:WILEY_ML3GV2_TO_JATSPMC version:6.4.8 mode:remove_FC converted:02.09.2024
==== Body
pmcDr. Takeuchi and Kitagawa 1 described the importance of artificial intelligence (AI) in surgical innovation. AI is rapidly gaining ground in various surgical fields worldwide. The current trajectory indicates that harnessing AI technologies can significantly improve patient care by reinforcing established practices and accelerating surgical innovation, offering a distinctive chance to explore potential advantages in providing health services to low‐ and middle‐income countries (LMICs) globally.

Large language models hold immense promise in revolutionizing medical education and emerging as indispensable assets in surgical practice. Medical students and surgeons could easily access a wealth of educational materials and clinical insights presented intuitively, enriching their understanding and proficiency. 2 AI technologies have demonstrated their effectiveness in tailoring surgical training, streamlining administrative duties, and creating practical and affordable simulation training programs tailored to the specific needs of diverse individuals. 3

Integrating machine learning algorithms in areas like big data analysis, computer vision, and operative robotics promises to revolutionize surgical patient risk assessment, surgical treatment, and postoperative monitoring, potentially enhancing patient outcomes through reductions in morbidity and mortality. 4 More importantly, immediate intra‐operative suggestions can assist surgeons in providing better evidence‐based treatment to surgical patients. As the key players in this transformation, surgeons have the power to grasp the basic principles of AI, understand its implications in healthcare, and explore avenues for integrating this technology. Collaboration with data scientists to capture comprehensive data and provide clinical context is pivotal to optimizing surgical care quality.

In the upcoming AI‐driven era, it is crucial to prioritize AI's conscientious and ethical utilization. This should be underscored by vigilant monitoring of data governance and potential patient safety risks during deployment. The implementation process must also address usability, pathway feasibility, and the crucial need for thorough evaluation of healthcare technology and evidence generation. When these may be perceived as obstacles to AI adoption, holistic implementation strategies promise to establish a robust framework for the widespread integration of AI across healthcare systems, ensuring its responsible and ethical use.

Global surgery encompasses a swiftly growing interdisciplinary domain dedicated to enhancing and ensuring fair access to quality surgical care within global healthcare frameworks. Initiatives within global surgery predominantly concentrate on bolstering capabilities, advocating for equitable access, facilitating educational programs, conducting research, and crafting policies tailored to the context of all countries. This is particularly significant for LMICs, where AI can potentially address deficiencies in surgical, anesthetic, and postoperative care, and is estimated to prevent 18 million mortalities annually, mainly in LMICs. 5 It holds promise in providing insights for governance, infrastructure development, and logistics prediction, bolstering the foundational pillars of global surgery.

The expansion of the interdisciplinary domain of AI in surgery brings with it a beacon of hope, aiming to bridge the gap in access to equitable quality of surgical care globally. Further research is imperative to ensure optimal and equitable AI utilization, overcoming obstacles such as data representativeness, training deficiencies, human hesitancy, and ethical considerations. Dealing with these challenges through a targeted, evidence‐driven strategy could assist LMICs in surmounting bureaucratic inefficiencies and establishing improved surgical systems.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflicts of interest for this article.

ETHICS STATEMENT

Approval of the research protocol: N/A.

Informed consent: N/A.

Registry and the Registration No. of the study/trial: N/A.

Animal studies: N/A.

ACKNOWLEDGMENTS

N/A.
==== Refs
REFERENCES

1 Takeuchi M , Kitagawa Y . Artificial intelligence and surgery. Ann Gastroenterol Surg. 2024;8 (1 ):4–5. 10.1002/ags3.12766 38250693
2 Guni A , Varma P , Zhang J , Fehervari M , Ashrafian H . Artificial intelligence in surgery: the future is now. Eur Surg Res. 2024;65 :22–39. 10.1159/000536393
3 Malhotra K , Wong BNX , Lee S , Franco H , Singh C , Silva LAC , et al. Role of artificial intelligence in global surgery: a review of opportunities and challenges. Cureus. 2023;15 (8 ):e43192. 10.7759/cureus.43192 37692604
4 Amin A , Cardoso SA , Suyambu J , Saboor HA , Cardoso RP , Husnain A , et al. Future of artificial intelligence in surgery: a narrative review. Cureus. 2024;16 (1 ):e51631. 10.7759/cureus.51631 38318552
5 Meara JG , Leather AJ , Hagander L , Alkire BC , Alonso N , Ameh EA , et al. Global surgery 2030: evidence and solutions for achieving health, welfare, and economic development. Lancet. 2015;386 (9993 ):569–624. 10.1016/S0140-6736(15)60160-X 25924834
