AIMC Topic: Nutrition Surveys

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A combined strategy of feature selection and machine learning to identify predictors of prediabetes.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To identify predictors of prediabetes using feature selection and machine learning on a nationally representative sample of the US population.

A Machine Learning Approach to Identification of Unhealthy Drinking.

Journal of the American Board of Family Medicine : JABFM
INTRODUCTION: Unhealthy drinking is prevalent in the United States, and yet it is underidentified and undertreated. Identifying unhealthy drinkers can be time-consuming and uncomfortable for primary care providers. An automated rule for identificatio...

Sarcopenia feature selection and risk prediction using machine learning: A cross-sectional study.

Medicine
The purpose of this study was to verify the usefulness of machine learning (ML) for selection of risk factors and development of predictive models for patients with sarcopenia.We collected medical records from Korean postmenopausal women based on Kor...

Impact of metformin on serum prostate-specific antigen levels: Data from the national health and nutrition examination survey 2007 to 2008.

Medicine
PURPOSE: A possible association between metformin use and the development of prostate cancer (PCa) has been reported. However, there is limited information on the impact of long-term metformin use on serum prostate-specific antigen (PSA) levels. We i...

[Serum 25-hydroxyvitamin D state in healthy children ten year minors old of Barranquilla metropolitan area].

Salud publica de Mexico
OBJETIVE: To evaluate the serum 25-hydroxyvitamin D (25-OH-D) levels in healthy children under 10 years of the Barranquilla metropolitan area.