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@@ -11,12 +11,12 @@ However, this data often exists only in clinical text, and not in any structured
## Features
### Pre-Annotations
-Sometimes concept mentions are simple and straightforward for algorithms to recognize. In these cases, we allow for pre-annotations; these pre-outline the suggested span of text and pre-label it. The user can then to choose to accept in just a single click, or modify or delete.
+Sometimes concept mentions are simple and straightforward for algorithms to recognize. In these cases, pre-annotations can save annotators time and energy. Pre-annotations outline the suggested span of text alongside its predicted label. The user can then to choose to accept the machine suggestion in just a single click, or modify or delete.
In this image, there are 3 pre-annotations: on flagyl, BUN, and NGT.
-Our system is flexible and allows the user to set the outputs of any clinical entity extraction system (MetaMap, cTAKES, ClinicalBERT) as pre-annotations. A user just provides the spans and expected labels in a CSV file; we provide scripts to generate these CSV's from dictionary lookups and from scispaCy.
+Our system can flexibly set the pre-annotations to the outputs of any clinical entity extraction system (MetaMap, cTAKES, ClinicalBERT). A user just provides the spans and expected labels in a CSV file; we provide scripts to generate these CSV's from dictionary lookups and from scispaCy.
### Recommendations