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Removing duplicated data As a post could include more than one hashtag, it could be extracted for multiple times.
Second stage First, we preprocessed data by removing duplicated tweets, stop words and applying filters as mentioned in step 2, "Second stage: classification" section.
Step 2 Consist of preprocessing the data as following: Removing duplicated data As a post could include more than one hashtag, it could be extracted for multiple times.
In addition, removing duplicated information from the collected data positively affects operational efficiency through appropriate use of medical IT systems such as EHR, personal health records, and health information exchange (HIE) systems.
This was done by iteratively removing duplicated domains until only a single (A-A) pair remained.
After removing duplicated reads (redundant information produced by PCR) using the SAMtools, an in-house cancer sequencing analysis pipeline (CSAP) was used to identify somatic mutations [ 15, 46].
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Considering the stage of postprocessed optimization several algorithms have been proposed to remove duplicated instances.
Thus, we remove duplicated tweets in order to avoid misleading results.
The counter should be smart enough to remove duplicated solutions and store all correct ones.
We removed duplicated publications that were identified in multiple databases.
Figure 5 Workflow for removing duplicate compounds.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com