> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.emtelligent.com/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.emtelligent.com/_mcp/server. # Identifying Terms of Interest in Radiology Reports ## Synopsis This query finds all terms labelled as **disease**, **findings**, and **morphologic abnormality** SNOMED entity types in the IMPRESSION section of Radiology reports. Entity type searches are less specific than concept search but are useful for finding entities for further analysis and filtering. ## Processing Requirements This query assumes that at least the following `emtellipro-db-client` processing options were enabled: * `--feature snomed-ontology` * `--store-sections-and-sentences` For this query, Radiology imaging studies were processed with the following document type: * `--category Radiology` * `--subcategory CT` ## Clinical Context Medical ontologies like SNOMED classify their concepts into semantic types such as `disorder`, `morphologic abnormality`, `findings`, `substance`, `procedure`, etc. The NLP API reports this information separately from the concept itself as the `entity_type` field in its output, which allows users to filter for concepts based on this information retrospectively. A common data science or clinical application scenario is one where a clinician wants to know, very generically, what medical problems a patient has had in their past. One simple way is to just search an Output Database for any concepts that are asserted, which have a SNOMED semantic type of `disorder`, `morphologic abnormality`, or `finding`. While this is a somewhat broad definition of medical problems (as many findings may be benign), it can be used with high-recall to identify almost any medical issue of concern that NLP API has coded with SNOMED CT. The results return can be reduced by searching for `disorder` only, or `disorder` and `morphologic abnormality` if higher precision is required. ## SQL query #### SQL ```sql ------------------------------------------------------------------------------------------------------------- -- Retrieve disease/findings/morphologic abnormality in IMPRESSION section of Radiology reports -- that are 'asserted' and 'certain' ------------------------------------------------------------------------------------------------------------- SELECT d.category AS document_category, c.concept_id, c.description, fe.section_name AS section, fe.text AS annotated_term, fe.polarity, fe.uncertainty, sl.text AS sentence FROM foundentity fe JOIN foundentityconcept fec ON fe.id = fec.found_entity_id JOIN concept c ON fec.concept_id = c.concept_id AND fec.concept_ontology = c.ontology JOIN foundentitytype fet on fe.id = fet.found_entity_id AND fet.ontology = 'snomed' JOIN foundentitylocation fel ON fe.id = fel.found_entity_id JOIN location l ON fel.location_id = l.id AND l.type_ = 'sentence' JOIN sentencelocation sl ON sl.id = l.location_id JOIN document d ON l.document_id = d.id WHERE c.ontology = 'snomed' AND fet.type_name IN ('disorder', 'finding', 'morphologic abnormality') -- Snomed CT entity types AND d.category = 'Radiology' AND fe.section_name = 'IMPRESSION' -- REPLACE: with section of interest e.g. FINDINGS, INDICATIONS AND fe.polarity = 'asserted' AND fe.uncertainty = 'certain'; -- LIMIT 1000; -- RECOMMENDED: for very large data sets ``` #### Microsoft SQL Server ```sql ------------------------------------------------------------------------------------------------------------- -- Retrieve disease/findings/morphologic abnormality in IMPRESSION section of Radiology reports -- that are 'asserted' and 'certain' ------------------------------------------------------------------------------------------------------------- SELECT TOP 1000 -- RECOMMENDED: for very large data sets d.category AS document_category, c.concept_id, c.description, fe.section_name AS section, fe.text AS annotated_term, fe.polarity, fe.uncertainty, sl.text AS sentence FROM foundentity fe JOIN foundentityconcept fec ON fe.id = fec.found_entity_id JOIN concept c ON fec.concept_id = c.concept_id AND fec.concept_ontology = c.ontology JOIN foundentitytype fet on fe.id = fet.found_entity_id AND fet.ontology = 'snomed' JOIN foundentitylocation fel ON fe.id = fel.found_entity_id JOIN location l ON fel.location_id = l.id AND l.type_ = 'sentence' JOIN sentencelocation sl ON sl.id = l.location_id JOIN document d ON l.document_id = d.id WHERE c.ontology = 'snomed' AND fet.type_name IN ('disorder', 'finding', 'morphologic abnormality') -- Snomed CT entity types AND d.category = 'Radiology' AND fe.section_name = 'IMPRESSION' -- REPLACE: with section of interest e.g. FINDINGS, INDICATIONS AND fe.polarity = 'asserted' AND fe.uncertainty = 'certain'; -- LIMIT 1000; -- RECOMMENDED: for very large data sets ``` #### Snowflake ```sql ------------------------------------------------------------------------------------------------------------- -- Retrieve disease/findings/morphologic abnormality in IMPRESSION section of Radiology reports -- that are 'asserted' and 'certain' ------------------------------------------------------------------------------------------------------------- WITH distinct_concepts AS (SELECT DISTINCT * FROM concept) SELECT d.category AS document_category, c.concept_id, c.description, fe.section_name AS section, fe.text AS annotated_term, fe.polarity, fe.uncertainty, sl.text AS sentence FROM foundentity fe JOIN foundentityconcept fec ON fe.id = fec.found_entity_id JOIN distinct_concepts c ON fec.concept_id = c.concept_id AND fec.concept_ontology = c.ontology JOIN foundentitytype fet on fe.id = fet.found_entity_id AND fet.ontology = 'snomed' JOIN foundentitylocation fel ON fe.id = fel.found_entity_id JOIN location l ON fel.location_id = l.id AND l.type_ = 'sentence' JOIN sentencelocation sl ON sl.id = l.location_id JOIN document d ON l.document_id = d.id WHERE c.ontology = 'snomed' AND fet.type_name IN ('disorder', 'finding', 'morphologic abnormality') -- Snomed CT entity types AND d.category = 'Radiology' AND fe.section_name = 'IMPRESSION' -- REPLACE: with section of interest e.g. FINDINGS, INDICATIONS AND fe.polarity = 'asserted' AND fe.uncertainty = 'certain'; -- LIMIT 1000; -- RECOMMENDED: for very large data sets ``` | document_category | concept_id | description | section | annotated_term | polarity | uncertainty | sentence | | ----------------- | ---------- | ------------------------------------------ | ---------- | ---------------------- | -------- | ----------- | ------------------------------------------------------------------------------------------------------------------------------------------------------- | | Radiology | 40199007 | Supine body position (finding) | IMPRESSION | supine | asserted | certain | No obvious pneumoperitoneum or bowel obstruction, but evaluation is limited on these supine views. | | Radiology | 64613007 | Inflammation of small intestine (disorder) | IMPRESSION | enteritis | asserted | certain | Several fluid-filled loops of jejunum are present compatible with mild enteritis. | | Radiology | 396347007 | Umbilical hernia (disorder) | IMPRESSION | umbilical hernia | asserted | certain | Fat containing umbilical hernia. | | Radiology | 197321007 | Steatosis of liver (disorder) | IMPRESSION | Fatty liver | asserted | certain | Fatty liver. | | Radiology | 89977008 | Increased thickness (finding) | IMPRESSION | thickening | asserted | certain | Subtle area of thickening of the lower rectal wall. | | Radiology | 300312006 | Lesion of rectum (disorder) | IMPRESSION | rectal wall thickening | asserted | certain | Subtle area of thickening of the lower rectal wall. | | Radiology | 76197007 | Hyperplasia (morphologic abnormality) | IMPRESSION | hyperplasia | asserted | certain | Multiple visualized nodes of the bilateral deep lateral cervical nodal chain, within normal size and morphology, most compatible with mild hyperplasia. | | Radiology | 4147007 | Mass (morphologic abnormality) | IMPRESSION | mass lesion | asserted | certain | Large, well demarcated mass lesion of the deep lobe of the left parotid gland, with probable involvement of the left facial nerve. | | Radiology | 53461003 | Normal size (finding) | IMPRESSION | normal size | asserted | certain | Multiple visualized nodes of the bilateral deep lateral cervical nodal chain, within normal size and morphology, most compatible with mild hyperplasia. | | Radiology | 312894000 | Osteopenia (disorder) | IMPRESSION | osteopenia | asserted | certain | Severe osteopenia. | ## Next steps To refine the query, one practical strategy that may be explored is to limit the search to specific report sections only. The section of the report where a diseased is mentioned typically provides important context that alters the interpretation and significance of the disease mention. The NLP API normalizes a large set of recognized section headings into standardized section names. To see a list of normalized section names present in your data, you can use the provided [here](/nlp/database/schema/core/document-tables#query-list-sections-by-report-category). Select one or more section names to use as a query constraint. To search for these entity types in a specific section, simply relace the `fe.section_name` WHERE clause with appropriate section name. ## Related links * [Entity-level Tables](/nlp/database/schema/core/entity-tables) * [List sections by report category](/nlp/database/schema/core/document-tables#query-list-sections-by-report-category).