Wake Forest University

About: Wake Forest University is a education organization based out in Winston-Salem, North Carolina, United States. It is known for research contribution in the topics: Population & Diabetes mellitus. The organization has 21499 authors who have published 48731 publications receiving 2246027 citations. The organization is also known as: Wake Forest College.

Guidelines of care for acne vulgaris management.

Abstract: Disclaimer Adherence to these guidelines will not ensure successful treatment in every situation. Furthermore, these guidelines should not be deemed inclusive of all proper methods of care or exclusive of other methods of care reasonably directed to obtaining the same results. The ultimate judgment regarding the propriety of any specific therapy must be made by the physician and the patient in light of all the circumstances presented by the individual patient.

A Comparison of Random Forest Variable Selection Methods for Classification Prediction Modeling.

Abstract: Random forest classification is a popular machine learning method for developing prediction models in many research settings. Often in prediction modeling, a goal is to reduce the number of variables needed to obtain a prediction in order to reduce the burden of data collection and improve efficiency. Several variable selection methods exist for the setting of random forest classification; however, there is a paucity of literature to guide users as to which method may be preferable for different types of datasets. Using 311 classification datasets freely available online, we evaluate the prediction error rates, number of variables, computation times and area under the receiver operating curve for many random forest variable selection methods. We compare random forest variable selection methods for different types of datasets (datasets with binary outcomes, datasets with many predictors, and datasets with imbalanced outcomes) and for different types of methods (standard random forest versus conditional random forest methods and test based versus performance based methods). Based on our study, the best variable selection methods for most datasets are Jiang's method and the method implemented in the VSURF R package. For datasets with many predictors, the methods implemented in the R packages varSelRF and Boruta are preferable due to computational efficiency. A significant contribution of this study is the ability to assess different variable selection techniques in the setting of random forest classification in order to identify preferable methods based on applications in expert and intelligent systems.

Management of High Blood Pressure in African Americans: Consensus Statement of the Hypertension in African Americans Working Group of the International Society on Hypertension in Blacks

Abstract: The purpose of this consensus statement is to offer primary care providers (including physicians, nurse practitioners, and physician assistants) a practical, evidence-based clinical tool for achieving blood pressure goals in African American patients. The need for specific recommendations for African Americans is highlighted by compelling evidence of a higher prevalence of hypertension and poorer cardiovascular and renal outcomes in this group than in white Americans. African Americans have disturbingly higher rates of cardiovascular mortality, stroke, hypertension-related heart disease, congestive heart failure, type 2 diabetes mellitus, hypertensive nephropathy, and end-stage renal disease (ESRD). 1,2 .