"latent patterns" is correct and usable in written English.
It is most often used in the context of data and machine learning, referring to patterns that exist in data but have not yet been identified. For example: "Data mining algorithms are often used to uncover latent patterns in large datasets."
The proposed approach is able to handle imprecise consumer perceptions and discover latent patterns to guide affective design.
Our approach to leverage latent patterns across genome-wide epigenetic datasets to infer the biological function will advance understanding of the genetics of human diseases by accelerating the interpretation of non-coding genomes.
Data were classified using full-text descriptions with Latent Dirichlet Allocation, and latent patterns emerging through the unsupervised learning process were modelled by company and year to create an overall view of patenting within the industry, and to forecast future trends.
The basic premise of the industry's offering is this: Hidden in that huge mass of enterprise data are latent patterns.
He understood that in music, innovation can arise through the detection of latent patterns in sources of disparate origin.
The analyses showed that the temporal variation of the 16 measures could be described by five latent patterns that reflected the complex patterning of intellectual functioning in extreme late life.
The Max-margin Latent Pattern Learning (MLPL) method is proposed to learn high-level semantic descriptions of latent action patterns as the output of our framework.
The geographical distribution of the risk of the PPH conditions is captured in a 36% by a unique latent pattern.
In our study we aimed not only to report the results of the interviews and their practical implications, but to identify the latent pattern of the data.
It remains surprising, however, that the psychology students were able to set up an efficient recoding scheme after only 15 minutes' training that allows easy shifting from overt to latent pattern recognition.
The distribution of this common latent pattern captures about the 36% of the total variability, and may be used to evaluate healthcare systems performance, as it allows detecting areas with homogeneously low or high risk of PPH admissions that may suggest hypotheses about possible causes (and possible interventions) to reduce the volume of PPH.
