Background In 2024, Ecuador faced its most severe drought in over six decades, severely disrupting hydroelectric power ...
Funding mechanisms impact the cost effectiveness of the science conducted, as extramural NIH grants to universities excel at producing papers and citations, while intramural NIH hiring more ...
Logistic regression is a statistical method used to model binary outcome variables, such as whether a patient recovers or not, using a set of predictors. There are many competing methods for ...
Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...
These were split into categories and their correlation with hypertension in this cohort was assessed using multivariate logistic regression. Python with libraries Numpy, Pandas, Scipy, Statsmodels, ...
ABSTRACT: Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language ...
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This set of notebooks enables the analysis of comorbidities associated with male infertility using structured EHR data. First, we identified nonoverlapping patients with male infertility and patients ...
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