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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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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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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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Urologia Journal, 2013
Predictive modeling is emerging as an important knowledge-based technology in healthcare. The interest in the use of predictive modeling reflects advances on different fronts such as the availability of health information from increasingly complex databases and electronic health records, a better understanding of causal or statistical predictors of ...
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Predictive modeling is emerging as an important knowledge-based technology in healthcare. The interest in the use of predictive modeling reflects advances on different fronts such as the availability of health information from increasingly complex databases and electronic health records, a better understanding of causal or statistical predictors of ...
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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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Connection Science, 2009
Modelling long-term dependencies in time series has proved very difficult to achieve with traditional machine-learning methods. This problem occurs when considering music data. In this paper, we introduce predictive models for melodies. We decompose melodic modelling into two subtasks.
Paiement, Jean-François +2 more
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Modelling long-term dependencies in time series has proved very difficult to achieve with traditional machine-learning methods. This problem occurs when considering music data. In this paper, we introduce predictive models for melodies. We decompose melodic modelling into two subtasks.
Paiement, Jean-François +2 more
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Approaches to predictive modeling
The Annals of Thoracic Surgery, 1994A four-component clinical model for process improvement is presented: (1) patient-related risk factors, (2) clinical processes ordered by the attending physician, (3) the hospital's execution of the physician's plan, and (4) the patient's outcome, or outcomes, resulting from the first three factors.
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Models for Prediction Purposes
Journal of Mental Science, 1959It is natural for psychiatrists and others dealing with mental patients to enquire what the prognosis is for a patient showing certain symptoms or syndromes of symptoms—taking age and the history of the patient's illness into account. The very fact that the symptoms generally form syndromes points to their interdependence to a greater or lesser degree,
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Structure prediction and modelling
Current Biology, 1992Cracking the second fundamental code of molecular biology (how the tertiary structure of a protein is determined by its amino acid sequence) remains an elusive goal. However, the impetus to establish credible approximations, if not a definitive solution to this relationship, has never been greater.
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Model Assessment for Predictive Classification Models
Communications in Statistics - Theory and Methods, 2010In this article, we present a novel methodology to assess predictive models for a binary target. In our opinion, the main weakness of the criteria proposed in the literature is not to take the financial costs of a wrong decision into account. The objective of this article is to derive the optimal cut-off in predictive classification models and to ...
UBERTI, PIERPAOLO, Figini S.
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