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Richard A. Levine

Researcher at San Diego State University

Publications -  87
Citations -  4763

Richard A. Levine is an academic researcher from San Diego State University. The author has contributed to research in topics: Markov chain Monte Carlo & Gibbs sampling. The author has an hindex of 28, co-authored 82 publications receiving 4379 citations. Previous affiliations of Richard A. Levine include Cornell University & New York Blood Center.

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C-Reactive protein predicts all-cause and cardiovascular mortality in hemodialysis patients.

TL;DR: Although values for blood urea nitrogen, creatinine, and normalized protein catabolic rate were significantly less among patients who died, these parameters, as well as cholesterol level and diabetes, were not important predictors of death in multivariate analysis.
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Fragile X Premutation Tremor/Ataxia Syndrome: Molecular, Clinical, and Neuroimaging Correlates

TL;DR: The clinical presentation of these patients, coupled with a specific lesion visible on magnetic resonance imaging and with neuropathological findings, affords a more complete delineation of this fragile X premutation-associated tremor/ataxia syndrome and distinguishes it from other movement disorders.
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Penetrance of the Fragile X–Associated Tremor/Ataxia Syndrome in a Premutation Carrier Population

TL;DR: It is demonstrated that older male carriers of premutation alleles of the FMR1 gene are at high risk of developing fragile X-associated tremor/ataxia syndrome (FXTAS), and older men with ataxia and intention tremor should be screened for the F MR1 mutation.
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Invasive species profiling? Exploring the characteristics of non-native fishes across invasion stages in California

TL;DR: A data base on fish invasions in catchments throughout California is developed that distinguishes among the establishment, spread and integration stages of the invasion process, and separates social and biological factors related to invasion success.
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Implementations of the Monte Carlo EM Algorithm

TL;DR: The Monte Carlo EM (MCEM) algorithm is a modification of the EM algorithm where the expectation in the E-step is computed numerically through Monte Carlo simulations and an automated rule is applied for increasing the Monte Carlo sample size whenthe Monte Carlo error overwhelms the EM estimate at any given iteration.