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The world is awash in data–images, websites, books, TikTok videos, and more–that contain important information about the world around us, information that statisticians and data scientists want to ...
Abstract: Technological advancements have made large-scale predictive analytics possible for early prediction of diseases through a much richer and more complicated reality of clinical data that was ...
Abstract: Hyperspectral images (HSIs) offer great potential for computational pathology. But, limited by the lack of adequate annotated data and the high spectral redundancy of HSIs, traditional ...
Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...
Priority Organization for Innovation and Excellence Laboratory for Data Sciences, Kumamoto University, 2-39-1, Kurokami, Chuo-ku, Kumamoto 860-8555, Japan ...
Objectives To estimate the shape of the causal relationship between body mass index (BMI) and mortality risk in a Mendelian randomisation framework. Design Mendelian randomisation analyses of two ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Chemometric methods are broadly used in the chemical and biochemical sectors.
fDepartment of Epidemiology and Data Science, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, Netherlands ...
Geothermal heat flow (GHF) data measured directly from boreholes are sparse. Purely physics-based models for geothermal heat flow prediction require various simplifications and are feasible only for ...
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