کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6926409 1449076 2018 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Federated learning of predictive models from federated Electronic Health Records
ترجمه فارسی عنوان
یادگیری فدرال از مدل های پیش بینی شده از سوابق سلامت الکترونیک فدرال
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
We test cPDS on the problem of predicting hospitalizations due to heart diseases within a calendar year based on information in the patients Electronic Health Records prior to that year. cPDS converges faster than centralized methods at the cost of some communication between agents. It also converges faster and with less communication overhead compared to an alternative distributed algorithm. In both cases, it achieves similar prediction accuracy measured by the Area Under the Receiver Operating Characteristic Curve (AUC) of the classifier. We extract important features discovered by the algorithm that are predictive of future hospitalizations, thus providing a way to interpret the classification results and inform prevention efforts.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Medical Informatics - Volume 112, April 2018, Pages 59-67
نویسندگان
, , , , , ,