دانلود و نمایش مقالات مرتبط با جراحی ارتوپدی::صفحه 1
بلافاصله پس از پرداخت دانلود کنید

با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد). 

نتیجه جستجو - جراحی ارتوپدی

تعداد مقالات یافته شده: 2
ردیف عنوان نوع
1 Surgical Phase Recognition Method with a Sequential Consistency for CAOS-AI Navigation System
روش تشخیص مرحله جراحی با یک سازگاری متوالی برای سیستم ناوبری CAOS-AI-2020
The procedure of orthopedic surgery is quite complicated, and many kinds of equipment have been used. Operating room nurses who deliver surgical instruments to surgeon are supposed to be forced to incur a heavy burden. There are some studies to recognize surgical phase with convolutional neural network (CNN) in minimally invasive laparoscopic surgery only. Previously, we proposed a computer-aided orthopedic surgery (CAOS)-AI navigation system based on CNN. However, the work propose a method to improve accuracy of phase recognition by considering temporal dependency of orthopedic surgery video acquired from surgeon-wearable video camera. The method estimates current surgical phase by combining both temporal dependency and convolutional-long-short term memory network (CNN-LSTM). Experimental results shows a phase recognition accuracy of 59.9% by the proposed method applied in unicomapartmenatal knee arthroplasty (UKA).
Keywords: Deep Learning | Computer-aided Orthopaedic Surgery | Operating Room Nurse | Phase Recognition
مقاله انگلیسی
2 Development of Machine Learning Algorithms for Prediction of Sustained Postoperative Opioid Prescriptions After Total Hip Arthroplasty
توسعه الگوریتم های یادگیری ماشین برای پیش بینی نسخه های افیونی پس از عمل پایدار پس از آرتروپلاستی کامل باسن-2019
Background: Postoperative recovery after total hip arthroplasty (THA) can lead to the development of prolonged opioid use but there are few tools for predicting this adverse outcome. The purpose of this study is to develop machine learning algorithms for preoperative prediction of prolonged opioid prescriptions after THA. Methods: A retrospective review of electronic health records was conducted at 2 academic medical centers and 3 community hospitals to identify adult patients who underwent THA for osteoarthritis between January 1, 2000 and August 1, 2018. Prolonged postoperative opioid prescriptions were defined as continuous opioid prescriptions after surgery to at least 90 days after surgery. Five machine learning algorithms were developed to predict this outcome and were assessed by discrimination, calibration, and decision curve analysis. Results: Overall, 5507 patients underwent THA, of which 345 (6.3%) had prolonged postoperative opioid prescriptions. The factors determined for prediction of prolonged postoperative opioid prescriptions were age, duration of opioid exposure, preoperative hemoglobin, and preoperative medications (antidepressants, benzodiazepines, nonsteroidal anti-inflammatory drugs, and beta-2-agonists). The elasticnet penalized logistic regression model achieved the best performance across discrimination (c-statistic ¼ 0.77), calibration, and decision curve analysis. This model was incorporated into a digital application able to provide both predictions and explanations (available at https://sorg-apps.shinyapps. io/thaopioid/). Conclusion: If externally validated in independent populations, the algorithms developed in this study could improve preoperative screening and support for THA patients at high risk for prolonged postoperative opioid prescriptions. Early identification and intervention in high-risk cases may mitigate the long-term adverse consequence of opioid dependence. Level of Evidence: III.
Keywords: arthroplasty | machine learning | opioid use | orthopedic surgery | prediction | total hip arthroplasty
مقاله انگلیسی
rss مقالات ترجمه شده rss مقالات انگلیسی rss کتاب های انگلیسی rss مقالات آموزشی
logo-samandehi
بازدید امروز: 10561 :::::::: بازدید دیروز: 0 :::::::: بازدید کل: 10561 :::::::: افراد آنلاین: 57