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| http://dx.doi.org/10.1186/s13049-024-01244-8 | DOI Listing |
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The triglyceride-glucose index and its obesity-related derivatives as predictors of all-cause and cardiovascular mortality in hypertensive patients: insights from NHANES data with machine learning analysis.
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Department of Cardiology, The Second Affiliated Hospital, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, People's Republic of China.
Background: Hypertension (HTN) is a global public health concern and a major risk factor for cardiovascular disease (CVD) and mortality. Insulin resistance (IR) plays a crucial role in HTN-related metabolic dysfunction, but its assessment remains challenging. The triglyceride-glucose (TyG) index and its derivatives (TyG-BMI, TyG-WC, and TyG-WHtR) have emerged as reliable IR markers.
View Article and Find Full Text PDFGenerative AI as a tool to accelerate the field of ecology.
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Center for Ecosystem Sentinels, Department of Biology, University of Washington, Seattle, WA, USA.
The emergence of generative artificial intelligence (AI) models specializing in the generation of new data with the statistical patterns and properties of the data upon which the models were trained has profoundly influenced a range of academic disciplines, industry and public discourse. Combined with the vast amounts of diverse data now available to ecologists, from genetic sequences to remotely sensed animal tracks, generative AI presents enormous potential applications within ecology. Here we draw upon a range of fields to discuss unique potential applications in which generative AI could accelerate the field of ecology, including augmenting data-scarce datasets, extending observations of ecological patterns and increasing the accessibility of ecological data.
View Article and Find Full Text PDFVirtual hospitals are rapidly being implemented internationally. Research has predominantly focused on clinical outcomes not implementation. We aimed to identify pre-implementation determinants to enable health services to tailor virtual hospital models, increasing likelihood of suitability, acceptability, uptake, clinical effectiveness, and sustainability.
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