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).
دسته بندی:
یادگیری عمیق - deep learning
سال انتشار:
2019
عنوان انگلیسی مقاله:
Preoperative Prediction of Value Metrics and a Patient-Specific Payment Model for Primary Total Hip Arthroplasty: Development and Validation of a Deep Learning Model
ترجمه فارسی عنوان مقاله:
پیش بینی قبل از عمل از معیارهای ارزش و یک مدل پرداخت خاص برای بیمار برای آرتروپلاستی کامل باسن اولیه: توسعه و اعتبارسنجی یک مدل یادگیری عمیق
منبع:
Sciencedirect - Elsevier - The Journal of Arthroplasty, 34 (2019) 2228-2235: doi:10:1016/j:arth:2019:04:055
نویسنده:
Prem N. Ramkumar, MD, MBA a, *, Jaret M. Karnuta a, Sergio M. Navarro b, Heather S. Haeberle c, Richard Iorio, MD d, Michael A. Mont, MD e, Brendan M. Patterson, MD, MBA a, Viktor E. Krebs, MD
چکیده انگلیسی:
Background: The primary objective was to develop and test an artificial neural network (ANN) that learns
and predicts length of stay (LOS), inpatient charges, and discharge disposition for total hip arthroplasty.
The secondary objective was to create a patient-specific payment model (PSPM) accounting for patient
complexity.
Methods: Using 15 preoperative variables from 78,335 primary total hip arthroplasty cases for osteoarthritis
from the National Inpatient Sample and our institutional database, an ANN was developed to
predict LOS, charges, and disposition. Validity metrics included accuracy and area under the curve of the
receiver operating characteristic curve. Predictive uncertainty was stratified by All Patient Refined comorbidity
cohort to establish the PSPM.
Results: The dynamic model demonstrated “learning” in the first 30 training rounds with areas under the
curve of 82.0%, 83.4%, and 79.4% for LOS, charges, and disposition, respectively. The proposed PSPM
established a risk increase of 2.5%, 8.9%, and 17.3% for moderate, major, and severe comorbidities,
respectively.
Conclusion: The deep learning ANN demonstrated “learning” with good reliability, responsiveness, and
validity in its prediction of value-centered outcomes. This model can be applied to implement a PSPM for
tiered payments based on the complexity of the case.
Keywords: deep learning | artificial intelligence | total hip | payment model | prediction
قیمت: رایگان
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