Artificial Intelligence and Machine Learning in General Surgery: A Narrative Review of Transformative Technologies
محل انتشار: مجله جراحی و تروما، دوره: 13، شماره: 2
سال انتشار: 1404
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 34
فایل این مقاله در 9 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_JSTR-13-2_002
تاریخ نمایه سازی: 29 تیر 1404
چکیده مقاله:
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.
کلیدواژه ها:
نویسندگان
Abolfazl Torabi
Medical Student, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Mohammad Ehsan Bayatpoor
General Surgery Department, Modarres Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Nasim Nouri
Medical Student, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Maryam Abbasi
General Surgery Department, Modarres Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Nasser Malekpour Alamdari
Critical Care Quality Improvement Research Center, Shahid Modarres Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
مراجع و منابع این مقاله:
لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :