**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*.