For each code, we look up its text description in MRCONSO.RRF (STR column). Since there might be multiple entries for the same code, we only keep the shortest string (with at least 4 characters) that satisfy the query condition: "SUPPRESS" NOT IN ('O', 'Y') AND ISPREF='Y' AND LAT='ENG'. For code with no description, they are mapped to NO_DEF. The mapping is stored as an OntologyCodeDictionary in ontology.db.
create_timelines.py shows an example of how to query per-patient timeline object with text descriptions.
test_patient.json shows an example output from a SynPUF patient.
Implementation for issue #24.
For each code, we look up its text description in MRCONSO.RRF (STR column). Since there might be multiple entries for the same code, we only keep the shortest string (with at least 4 characters) that satisfy the query condition:
"SUPPRESS" NOT IN ('O', 'Y') AND ISPREF='Y' AND LAT='ENG'. For code with no description, they are mapped toNO_DEF. The mapping is stored as anOntologyCodeDictionaryinontology.db.create_timelines.pyshows an example of how to query per-patient timeline object with text descriptions.test_patient.jsonshows an example output from a SynPUF patient.