MedNorm2SnomedCT2UMLS

Paper on Mednorm and harmonisation: https://aclanthology.org/W19-3204.pdf

The medical concept normalisation task aims to map textual descriptions to standard terminologies such as SNOMED-CT or MedDRA.

Existing publicly available datasets annotated using different terminologies cannot be simply merged and utilised, and therefore become less
valuable when developing machine learningbased concept normalisation systems. 

To address that, we designed a data harmonisation pipeline and engineered a corpus of 27,979 textual descriptions simultaneously mapped to both MedDRA and SNOMED-CT, 
sourced from five publicly available datasets across biomedical and social media domains.

license:mit region:us
{"license": "mit"}
TAGS
#license-mit #region-us 

MedNorm2SnomedCT2UMLS

Paper on Mednorm and harmonisation: URL

The medical concept normalisation task aims to map textual descriptions to standard terminologies such as SNOMED-CT or MedDRA.

Existing publicly available datasets annotated using different terminologies cannot be simply merged and utilised, and therefore become less
valuable when developing machine learningbased concept normalisation systems. 

To address that, we designed a data harmonisation pipeline and engineered a corpus of 27,979 textual descriptions simultaneously mapped to both MedDRA and SNOMED-CT, 
sourced from five publicly available datasets across biomedical and social media domains.

TAGS
#license-mit #region-us 

passage: TAGS
#license-mit #region-us 
