Results, classification, Early Risk, all models
Development and use of prediction models for classification of cardiovascular risk of remote indigenous Australians
... CVD risk. Table 1 provides summary statistics of these risk factors and the 5-year survival rate of an average ...of all variables included in the full ...the risk factors in the primary and ...
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Development and use of prediction models for classification of cardiovascular risk of remote Indigenous Australians
... CVD risk. Table 1 provides summary statistics of these risk factors and the 5-year survival rate of an average ...of all variables included in the full ...the risk factors in the primary and ...
10
Stroke Risk Prediction through Non linear Support Vector Classification Models
... possible risk of Cerebro Vascular Accident (CVA) or Stroke by subjecting the risk factors to Support Vector Machines ...of risk contributed by the factors is imperative for early prediction ...
7
Cooking is All About People: Comment Classification on Cookery Channels Using Bert and Classification Models (Malayalam-English Mix-Code)
... 2.3.4 Aksara Jawa Text Detection in Scene Images using Convolutional Neural Network This thesis [1] deals with the preservation of Aksara Jawa text in the loss heritage culture. Aksara Jawa text is an ancient Javanese ...
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Malaria in central Vietnam: analysis of risk factors by multivariate analysis and classification tree models
... malaria risk factors potentially vulnerable to control activities with their expected ...mial models (e.g. logistic regression) as they do not rank risk factors according to their importance, ...
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Risk classification for claim counts and losses using regression models for location, scale and shape
... of risk factors was widely accepted for ratemaking. Also, the results for the location parameter of the claim frequency/severity models are in line with the existing results, based on the ...
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Intelligible Models for Classification and Regression
... The bias-variance results for the six regression datasets are shown in Figure 6. We can see that methods based on regression splines have very low variance, but sometimes at the expense of increased bias, while ...
9
CAS: Risk Classification for Claim Counts and Losses Using Regression Models for Location, Scale and Shape
... of risk factors was widely accepted for ratemaking. Also, the results for the location parameter of the claim frequency/severity models are in line with the existing results, based on the ...
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Risk Classification (for All Practice Areas)
... Several commentators expressed opinions regarding the requirement that the actuary should disclose whether quantitative analyses were performed relative to items being disclosed. One commentator expressed strong ...
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Risk Classification in High Dimensional Survival Models
... Although it was not used in our analysis, TCGA provides other datasets, includ- ing gene-level expression estimates. We aggregated the isoform expression dataset at the gene-level and compared it to the provided ...
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Asymptotic results for renewal risk models with risky investments
... discrete-time risk process with stochastic returns on investments and also investigates the transition to the continuous-time ...continuous-time risk process with stochastic returns on investments, given ...
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Exact and asymptotic results for insurance risk models with surplus-dependent premiums
... that all forcing functions are chosen so that all infinite integrals have a finite value (this will be the case in all the examples treated ...
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Diagnosis, prognosis and classification of early arthritis: results of a systematic review informing the 2016 update of the EULAR recommendations for the management of early arthritis
... Current SLR The aim of the current search was to retrieve studies evaluating the diagnostic value of laboratory tests and/ or imaging tests in patients presenting with EA in terms of classifying them as RA or as other in ...
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Ouroboros: early identification of at-risk students without models based on legacy data
... When all data are available, the best predictor makes use of actual performance either by: (a) student study history measured ...with models trained on the previous presentation of the same course. To ...
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Models for early prediction of at-risk students in a course using standards-based grading
... academic early warning systems ...most early warning systems have been designed for online courses or rely heavily on Course Management System (CMS) access data ...Third, early warning systems do not ...
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Developing predictive models for early detection of at-risk students on distance learning modules
... 2. Previous work with OU data Decision trees have proved a fairly popular method for exploring the potential for building predictive models from student data (see Baradawaj and Pal, 2011; Pandey and Sharma, 2013; ...
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Risk Classification for Claim Counts and Losses Using Regression Models for Location, Scale and Shape
... The models brie‡y described above assume that only the mean is modelled as a function of risk ...that all the parameters of the claim frequency/severity distributions can be modelled as functions of ...
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Classification of Network Formation Models
... network models in general also applies to social network formation models in ...this models are often not modelled to describe really existing social networks, but researchers often prefer to find ...
22
The multiple sclerosis risk sharing scheme monitoring study - early results and lessons for the future
... MS Risk Sharing Scheme ...the Risk Sharing ...of all entered data at the time of the analysis reported here, locking the database on 31st Janu- ary ...
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The Multiple Sclerosis Risk Sharing Scheme Monitoring Study – early results and lessons for the future
... MS Risk Sharing Scheme ...the Risk Sharing ...of all entered data at the time of the analysis reported here, locking the database on 31st Janu- ary ...
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