Sentence examples for data recognized from inspiring English sources

Exact(6)

Our data recognized that compound 6p could be considered as a starting point for development of new JmjC inhibitors.

The level of detail in Apple's Health system is extensive for a consumer product, with sixty different types of data recognized — from blood glucose, to oxygen saturation, to dietary cholesterol, to respiration rate.

Because of advances in image recognition technology, Google Photos (and some other photo apps) have built advanced search capabilities that let you pull up not places, things, people, and more, using data recognized in the image itself.

The data used for these investigations accrued from an eighteen year Provinicial cohort of data, recognized externally for its excellence.

A study of grey neck species [ 15], mainly based on karyotypic data, recognized at least seven species of this group, A. brumbacki, A. griseimembra, A. lemurinus, A. trivirgatus, A. vociferans, A. zonalis and a presumably novel one named A. jorgehernandezi.

Considering that supermarkets and grocery stores are no longer the only shopping opportunities for fruit and vegetables, BVFEP data recognized the emergence of new and changing food store formats [ 65].

Similar(54)

I want the students to become sophisticated consumers of data, recognizing the strengths and weaknesses of the various data sets available to solve particular problems.

"Being able to analyze data, recognize patterns, summarize results, break down problems in the simplest way these are the kinds of things I learned prior to joining industry".

It will happen through the use of machine learning algorithms that absorb a large volume of data, recognize patterns and apply statistical probabilities to choose the course of action most likely to result in a successful outcome.

It is a comparative accuracy assessment, in which each modeled dataset is compared to a set of reference data, recognizing both the potential for error in reference data, and probable differences in spatial support between the datasets.

Basically, the term refers to a program's ability to study data, recognize patterns and then make predictions based on that data.

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