Article in Press
Back to the articles list |
Back to browse issues page
Abolfazl Torabi 
, Mohammad Ehsan Bayatpoor , Nasim Nouri , Maryam Abbasi , Nasser Malekpour Alamdari *
, Mohammad Ehsan Bayatpoor , Nasim Nouri , Maryam Abbasi , Nasser Malekpour Alamdari *
Critical Care Quality Improvement Research Center, Shahid Modarres Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Abstract: (234 Views)
As computational power and data science continue to advance at an unprecedented pace, their influence is reshaping various scientific fields, including medicine. While machine learning (ML) has already made substantial strides in diagnostic areas, such as radiology and pathology, its role in surgery is an emerging frontier. This narrative review examines the current literature on artificial intelligence (AI) and ML applications in general surgery, with a particular focus on their ability to support clinical decision-making, streamline surgical workflows, and improve patient outcomes. Key topics explored include predicting discharge dates, assessing preoperative risk for both elective and emergency surgeries, and the innovative use of AI in resident education and simulation training. By evaluating these developments, the practical challenges, ethical concerns, and future prospects of integrating AI into surgical practice were discussed. Ultimately, this review highlights the transformative potential of AI and ML in surgery, suggesting that these technologies will play a key role in enhancing care quality and the professional growth of surgeons.
Type of Study: Review |
Subject:
General Surgery
Received: 2024/09/25 | Accepted: 2025/03/20 | ePublished ahead of print: 2025/04/12
Received: 2024/09/25 | Accepted: 2025/03/20 | ePublished ahead of print: 2025/04/12
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
Attribution-NoneCommercial CC BY-NC
