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Development and external validation of a predictive model for in-hospital mortality in patients with liver cirrhosis and sepsis. [PDF]
Sci RepHu Y, Zhang L, Yin J.
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Development and Validation of a Predictive Model for Surgical Site Infection in Open Hand Injuries. [PDF]
Infect Drug ResistNie X +7 more
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Psychometrika, 2006
Multilevel models are proven tools in social research for modeling complex, hierarchical systems. In multilevel modeling, statistical inference is based largely on quantification of random variables. This paper distinguishes among three types of random variables in multilevel modeling—model disturbances, random coefficients, and future response ...
Frees, Edward W., Kim, Jee-Seon
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Multilevel models are proven tools in social research for modeling complex, hierarchical systems. In multilevel modeling, statistical inference is based largely on quantification of random variables. This paper distinguishes among three types of random variables in multilevel modeling—model disturbances, random coefficients, and future response ...
Frees, Edward W., Kim, Jee-Seon
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MODEL IMPERFECTION AND PREDICTING PREDICTABILITY
International Journal of Bifurcation and Chaos, 2013It has been argued that Lyapunov exponents as a measure of predictability are of limited value because they only provide a global average. Characterizing an attractor by a distribution of times for initial uncertainties to increase by a factor of q has been suggested as a more useful alternative.
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Nomograms as predictive models
Seminars in Urologic Oncology, 2002Nomograms are valuable tools for estimating the likelihood of cancer being diagnosed, the pathologic features of a localized cancer, and the prognosis of a patient after treatment. Although the available nomograms are reasonably accurate, better predictive factors including additional clinical factors and new molecular analyses are needed to improve ...
James A, Eastham +2 more
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Structure prediction and modelling
Current Opinion in Biotechnology, 1991Protein structure prediction from sequence remains a major goal in molecular biology. The methods described in this review concentrate on deriving structural information through the detection of similarities between a test sequence and a database of known structures. Such methods are often referred to as knowledge-based strategies reflecting the use of
M B, Swindells, J M, Thornton
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12 International Workshop on Software Technology and Engineering Practice (STEP'04), 2006
A predictive software model (PSM) is any model extracted from software engineering data that can be readily used to make a prediction regarding some aspect of a software system. In this paper, we present some well known applications of predictive software models, and propose new potential applications for PSMs.
Jelber Sayyad-Shirabad +2 more
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A predictive software model (PSM) is any model extracted from software engineering data that can be readily used to make a prediction regarding some aspect of a software system. In this paper, we present some well known applications of predictive software models, and propose new potential applications for PSMs.
Jelber Sayyad-Shirabad +2 more
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