کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6920621 1447925 2018 20 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Studies in the extensively automatic construction of large odds-based inference networks from structured data. Examples from medical, bioinformatics, and health insurance claims data
ترجمه فارسی عنوان
مطالعات در ساخت و بکارگیری اتوماتیک شبکه های استنتاج مبتنی بر شانس بزرگ از داده های ساخت یافته. نمونه هایی از اطلاعات پزشکی، بیوانفورماتیک و بیمه درمانی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
Theoretical and methodological principles are presented for the construction of very large inference nets for odds calculations, composed of hundreds or many thousands or more of elements, in this paper generated by structured data mining. It is argued that the usual small inference nets can sometimes represent rather simple, arbitrary estimates. Examples of applications in clinical and public health data analysis, medical claims data and detection of irregular entries, and bioinformatics data, are presented. Construction of large nets benefits from application of a theory of expected information for sparse data and the Dirac notation and algebra. The extent to which these are important here is briefly discussed. Purposes of the study include (a) exploration of the properties of large inference nets and a perturbation and tacit conditionality models, (b) using these to propose simpler models including one that a physician could use routinely, analogous to a “risk score”, (c) examination of the merit of describing optimal performance in a single measure that combines accuracy, specificity, and sensitivity in place of a ROC curve, and (d) relationship to methods for detecting anomalous and potentially fraudulent data.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Biology and Medicine - Volume 95, 1 April 2018, Pages 147-166
نویسندگان
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