دوره 13، شماره 2 - ( 3-1404 )
جلد 13 شماره 2 صفحات 54-46 |
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Torabi A, Bayatpoor M E, Nouri N, Abbasi M, Malekpour Alamdari N. Artificial Intelligence and Machine Learning in General Surgery: A Narrative Review of Transformative Technologies. J Surg Trauma 2025; 13 (2) :46-54
URL: http://jsurgery.bums.ac.ir/article-1-452-fa.html
URL: http://jsurgery.bums.ac.ir/article-1-452-fa.html
Artificial Intelligence and Machine Learning in General Surgery: A Narrative Review of Transformative Technologies. نشریه جراحی و تروما. 1404; 13 (2) :46-54
چکیده: (516 مشاهده)
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.
نوع مطالعه: مروری |
موضوع مقاله:
جراحی عمومی
دریافت: 1403/7/4 | پذیرش: 1403/12/30 | انتشار الکترونیک پیش از انتشار نهایی: 1404/1/23 | انتشار: 1404/3/27
دریافت: 1403/7/4 | پذیرش: 1403/12/30 | انتشار الکترونیک پیش از انتشار نهایی: 1404/1/23 | انتشار: 1404/3/27
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