Diagnostic and Statistical Manual of Mental Disorders
The fifth edition of the <italic>Diagnostic and Statistical Manual of Mental Disorders</italic> of the American Psychiatric Association is referred to as DSM-5<italic>™</italic>...
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The fifth edition of the <italic>Diagnostic and Statistical Manual of Mental Disorders</italic> of the American Psychiatric Association is referred to as DSM-5<italic>™</italic>...
Abstract This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the Inter...
An approach for electronic structure calculations is described that generalizes both the pseudopotential method and the linear augmented-plane-wave (LAPW) method in a natural wa...
SUMMARY We propose a new method for estimation in linear models. The ‘lasso’ minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients b...
Understanding sources of sustained competitive advantage has become a major area of research in strategic management. Building on the assumptions that strategic resources are he...
A general formula ( α ) of which a special case is the Kuder-Richardson coefficient of equivalence is shown to be the mean of all split-half coefficients resulting from differen...
Content analysis is a widely used qualitative research technique. Rather than being a single method, current applications of content analysis show three distinct approaches: con...
Abstract Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort ...
Systematic reviews and meta-analyses have become increasinglyimportant in health care. Clinicians readthem to keep up to date with their field (1, 2), and they areoften used as ...
The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation o...
Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, ex...