Ambiguity in medical concept normalization: An analysis of types and coverage in electronic health record datasets

Denis Newman-Griffis, Guy Divita, Bart Desmet, Ayah Zirikly, Carolyn Rosé & Eric Fosler-Lussier
Objective: Normalizing mentions of medical concepts to standardized vocabularies is a fundamental component of clinical text analysis. Ambiguity—words or phrases that may refer to different concepts—has been extensively researched as part of information extraction from biomedical literature, but less is known about the types and frequency of ambiguity in clinical text. This study characterizes the distribution and distinct types of ambiguity exhibited by benchmark clinical concept normalization datasets, in order to identify directions for advancing...
1 citation reported since publication in 2020.
31 views reported since publication in 2020.

These counts follow the COUNTER Code of Practice, meaning that Internet robots and repeats within a certain time frame are excluded.
What does this mean?
4 downloads reported since publication in 2020.

These counts follow the COUNTER Code of Practice, meaning that Internet robots and repeats within a certain time frame are excluded.
What does this mean?