Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Identifying biomarkers with predictive value for disease risk stratification is an important task in epidemiology.  describes an application of Bayesian linear survival regression to model cardiovascular event risk in diabetic individuals with measurements available on 55 candidate biomarkers.  extend the survival model to include data from a larger set of non-diabetic individuals in an effort to increase the predictive performance for the diabetic subpopulation.  compare the Gaussian, Laplace and horseshoe shrinkage priors, and find that the last has the best predictive performance and shrinks strong predictors less than the others.  implement the projection predictive covariate selection approach of Dupuis and Robert (2003) to further search for small sets of predictive biomarkers that could provide cost-efficient prediction without significant loss in performance. In passing,  present a derivation of the projective covariate selection in Bayesian decision theoretic framework.
['Tomi Peltola', 'Aki S. Havulinna', 'Veikko Salomaa', 'Aki Vehtari']
I am writing a research paper on a idea Hierarchical Bayesian survival analysis and projective covariate selection in cardiovascular event risk prediction
[{"from": "human", "value": "I am writing a research paper on a idea Hierarchical Bayesian survival analysis and projective covariate selection in cardiovascular event risk prediction"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Identifying biomarkers with predictive value for disease risk stratification is an important task in epidemiology.  describes an application of Bayesian linear survival regression to model cardiovascular event risk in diabetic individuals with measurements available on 55 candidate biomarkers.  extend the survival model to include data from a larger set of non-diabetic individuals in an effort to increase the predictive performance for the diabetic subpopulation.  compare the Gaussian, Laplace and horseshoe shrinkage priors, and find that the last has the best predictive performance and shrinks strong predictors less than the others.  implement the projection predictive covariate selection approach of Dupuis and Robert (2003) to further search for small sets of predictive biomarkers that could provide cost-efficient prediction without significant loss in performance. In passing,  present a derivation of the projective covariate selection in Bayesian decision theoretic framework."}]