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pro vyhledávání: '"E L, Eisenstein"'
Publikováno v:
Journal of Nuclear Cardiology. 3:538-545
This review presents a brief overview of existing diagnostic and prognostic methodologies to be used for the evaluation of patients undergoing noninvasive testing. In part I of this review, we will present methods for use of logistic and Cox regressi
Autor:
E L, Eisenstein, C F, Bethea
Publikováno v:
Health care management science. 2(4)
We introduce a technique for patient mix-adjusting x charts and compared differences between unadjusted and patient mix-adjusted results. Our data came from coronary artery bypass graft (CABG) surgery patients at Baptist Medical Center, Oklahoma City
Autor:
E L, Eisenstein, E D, Peterson, J G, Jollis, B E, Tardiff, R M, Califf, J D, Knight, D B, Mark
Publikováno v:
Proceedings : a conference of the American Medical Informatics Association. AMIA Fall Symposium.
Newer pharmacologic agents have demonstrated significant clinical and economic benefit in high-risk percutaneous transluminal coronary angioplasty (PTCA) patients. However, the higher costs of these agents may prohibit their use in lower-risk coronar
Autor:
E L, Eisenstein, F, Alemi
Publikováno v:
Proceedings : a conference of the American Medical Informatics Association. AMIA Fall Symposium.
Accurately risk-stratifying patients is a key component of health care outcomes assessment. And, many health care organizations increasingly are relying upon automated means for assistance in making patient risk-stratification decisions. Unfortunatel
Autor:
E L, Eisenstein, J W, Hales
Publikováno v:
Proceedings. Symposium on Computer Applications in Medical Care.
This paper describes a healthcare cost accounting system which is under development at Duke University Medical Center. Our approach differs from current practice in that this system will dynamically adjust its resource usage estimates to compensate f
Autor:
E L, Eisenstein, F, Alemi
Publikováno v:
Proceedings. Symposium on Computer Applications in Medical Care.
This paper examines the influences of situational and model factors upon the accuracy of Bayesian learning systems. In particular, it is concerned with the impact of variations in training sample size, number of attributes, choice of Bayesian model,