File: //usr/local/aws-cli/v2/dist/awscli/examples/comprehendmedical/infer-snomedct.rst
**Example: To detect entities and link to the SNOMED CT Ontology directly from text**
The following ``infer-snomedct`` example shows how to detect medical entities and link them to concepts from the 2021-03 version of the Systematized Nomenclature of Medicine, Clinical Terms (SNOMED CT). ::
aws comprehendmedical infer-snomedct \
--text "The patient complains of abdominal pain, has a long-standing history of diabetes treated with Micronase daily."
Output::
{
"Entities": [
{
"Id": 3,
"BeginOffset": 26,
"EndOffset": 40,
"Score": 0.9598260521888733,
"Text": "abdominal pain",
"Category": "MEDICAL_CONDITION",
"Type": "DX_NAME",
"Traits": [
{
"Name": "SYMPTOM",
"Score": 0.6819021701812744
}
]
},
{
"Id": 4,
"BeginOffset": 73,
"EndOffset": 81,
"Score": 0.9905840158462524,
"Text": "diabetes",
"Category": "MEDICAL_CONDITION",
"Type": "DX_NAME",
"Traits": [
{
"Name": "DIAGNOSIS",
"Score": 0.9255214333534241
}
]
},
{
"Id": 1,
"BeginOffset": 95,
"EndOffset": 104,
"Score": 0.6371926665306091,
"Text": "Micronase",
"Category": "MEDICATION",
"Type": "BRAND_NAME",
"Traits": [],
"Attributes": [
{
"Type": "FREQUENCY",
"Score": 0.9761165380477905,
"RelationshipScore": 0.9984188079833984,
"RelationshipType": "FREQUENCY",
"Id": 2,
"BeginOffset": 105,
"EndOffset": 110,
"Text": "daily",
"Category": "MEDICATION",
"Traits": []
}
]
}
],
"UnmappedAttributes": [],
"ModelVersion": "1.0.0"
}
For more information, see `InferSNOMEDCT <https://docs.aws.amazon.com/comprehend-medical/latest/dev/ontology-linking-snomed.html>`__ in the *Amazon Comprehend Medical Developer Guide*.