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# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
"""
FILE: sample_finding_inference.py
DESCRIPTION:
The sample_finding_inference.py module processes a sample radiology document with the Radiology Insights service.
It will initialize a RadiologyInsightsClient, build a Radiology Insights request with the sample document,
submit it to the client, RadiologyInsightsClient, and display
-the Finding resource type,
-the Finding ID,
-the Finding status,
-the Finding category code,
-the Finding code,
-the Finding interpretation,
-the Finding components,
-the Finding component code,
-the Finding component value codeable concept,
-the Finding component value coding,
-the Finding component value boolean,
-the Finding component value quantity,
-the Inference extensions,
-the Inference extension URL,
-the Inference extension value string,
-the Inference extension section
USAGE:
1. Set the environment variables with your own values before running the sample:
- AZURE_HEALTH_INSIGHTS_ENDPOINT - the endpoint to your source Health Insights resource.
- For more details how to use DefaultAzureCredential, please take a look at https://learn.microsoft.com/python/api/azure-identity/azure.identity.defaultazurecredential
2. python sample_finding_inference.py
"""
import datetime
import os
import uuid
from azure.identity import DefaultAzureCredential
from azure.healthinsights.radiologyinsights import RadiologyInsightsClient
from azure.healthinsights.radiologyinsights import models
def radiology_insights_sync() -> None:
credential = DefaultAzureCredential()
ENDPOINT = os.environ["AZURE_HEALTH_INSIGHTS_ENDPOINT"]
job_id = str(uuid.uuid4())
radiology_insights_client = RadiologyInsightsClient(endpoint=ENDPOINT, credential=credential)
doc_content1 = """FINDINGS:
In the right upper lobe, there is a new mass measuring 5.6 x 4.5 x 3.4 cm.
A lobulated soft tissue mass is identified in the superior right lower lobe abutting the major fissure measuring 5.4 x 4.3 x 3.7 cm (series 3 image 94, coronal image 110).
A 4 mm nodule in the right lower lobe (series 3, image 72) is increased dating back to 6/29/2012. This may represent lower lobe metastasis.
IMPRESSION: 4 cm pulmonary nodule posterior aspect of the right upper lobe necessitating additional imaging as described."""
# Create ordered procedure
procedure_coding = models.Coding(
system="Https://loinc.org",
code="24627-2",
display="CT CHEST",
)
procedure_code = models.CodeableConcept(coding=[procedure_coding])
ordered_procedure = models.OrderedProcedure(description="CT CHEST", code=procedure_code)
# Create encounter
start = datetime.datetime(2021, 8, 28, 0, 0, 0, 0)
end = datetime.datetime(2021, 8, 28, 0, 0, 0, 0)
encounter = models.PatientEncounter(
id="encounter2",
class_property=models.EncounterClass.IN_PATIENT,
period=models.TimePeriod(start=start, end=end),
)
# Create patient info
birth_date = datetime.date(1959, 11, 11)
patient_info = models.PatientDetails(sex=models.PatientSex.FEMALE, birth_date=birth_date)
# Create author
author = models.DocumentAuthor(id="author2", full_name="authorName2")
create_date_time = datetime.datetime(2024, 2, 19, 0, 0, 0, 0, tzinfo=datetime.timezone.utc)
patient_document1 = models.PatientDocument(
type=models.DocumentType.NOTE,
clinical_type=models.ClinicalDocumentType.RADIOLOGY_REPORT,
id="doc2",
content=models.DocumentContent(source_type=models.DocumentContentSourceType.INLINE, value=doc_content1),
created_at=create_date_time,
specialty_type=models.SpecialtyType.RADIOLOGY,
administrative_metadata=models.DocumentAdministrativeMetadata(
ordered_procedures=[ordered_procedure], encounter_id="encounter2"
),
authors=[author],
language="en",
)
# Construct patient
patient1 = models.PatientRecord(
id="patient_id2",
details=patient_info,
encounters=[encounter],
patient_documents=[patient_document1],
)
# Create a configuration
configuration = models.RadiologyInsightsModelConfiguration(verbose=False, include_evidence=True, locale="en-US")
# Construct the request with the patient and configuration
patient_data = models.RadiologyInsightsJob(
job_data=models.RadiologyInsightsData(patients=[patient1], configuration=configuration)
)
# Health Insights Radiology Insights
try:
poller = radiology_insights_client.begin_infer_radiology_insights(
id=job_id,
resource=patient_data,
)
radiology_insights_result = poller.result()
display_finding(radiology_insights_result)
except Exception as ex:
raise ex
def display_finding(radiology_insights_result):
for patient_result in radiology_insights_result.patient_results:
counter = 0
for ri_inference in patient_result.inferences:
if ri_inference.kind == models.RadiologyInsightsInferenceType.FINDING:
counter += 1
print(f"Finding {counter} Inference found")
fin = ri_inference.finding
for attribute in dir(fin):
if attribute.startswith("_") or callable(getattr(fin, attribute)):
continue
elif attribute == "resource_type" and fin.resource_type is not None:
print(f"Finding {counter}: Resource Type: {fin.resource_type}")
elif attribute == "id" and fin.id is not None:
print(f"Finding {counter}: ID: {fin.id}")
elif attribute == "status" and fin.status is not None:
print(f"Finding {counter}: Status: {fin.status}")
elif attribute == "category" and fin.category is not None:
for cat in fin.category:
if cat.coding is not None:
for code in cat.coding:
if code.code is not None and code.display is not None:
print(
f"Finding {counter}: Category Code: {code.system} {code.code} {code.display}"
)
elif attribute == "code" and fin.code is not None:
for code in fin.code.coding:
if code.code is not None and code.display is not None:
print(f"Finding {counter}: Code: {code.system} {code.code} {code.display}")
elif attribute == "interpretation" and fin.interpretation is not None:
for interpretation in fin.interpretation:
for code in interpretation.coding:
if code.code is not None and code.display is not None:
print(
f"Finding {counter}: Interpretation: {code.system} {code.code} {code.display}"
)
elif attribute == "component" and fin.component is not None:
print(f"Finding {counter}: COMPONENTS:")
for component in fin.component:
for attribute in dir(component):
if attribute.startswith("_") or callable(getattr(component, attribute)):
continue
if attribute == "code" and component.code is not None:
for code in component.code.coding:
if code.code is not None and code.display is not None:
print(
f"Finding {counter}: COMPONENTS: Code: {code.system} {code.code} {code.display}"
)
elif (
attribute == "value_codeable_concept"
and component.value_codeable_concept is not None
):
for code in component.value_codeable_concept.coding:
if code.code is not None and code.display is not None:
print(
f"Finding {counter}: COMPONENTS: Value Codeable Concept: {code.system} {code.code} {code.display}"
)
elif attribute == "value_coding" and component.value_coding is not None:
for code in component.value_coding.coding:
if code.code is not None and code.display is not None:
print(
f"Finding {counter}: COMPONENTS: Value Coding: {code.system} {code.code} {code.display}"
)
elif attribute == "value_boolean" and component.value_boolean is not None:
print(f"Finding {counter}: COMPONENTS: Value Boolean: {component.value_boolean}")
elif attribute == "value_quantity" and component.value_quantity is not None:
for attribute in dir(component.value_quantity):
if (
not attribute.startswith("_")
and not callable(getattr(component.value_quantity, attribute))
and getattr(component.value_quantity, attribute) is not None
):
print(
f"Finding {counter}: COMPONENTS: Value Quantity: {attribute.capitalize()}: {getattr(component.value_quantity, attribute)}"
)
inference_extension = ri_inference.extension
if inference_extension is not None:
print(f"Finding {counter}: INFERENCE EXTENSIONS:")
for extension in inference_extension:
for attribute in dir(extension):
if attribute.startswith("_") or callable(getattr(extension, attribute)):
continue
elif attribute == "extension" and extension.extension is not None:
for sub_extension in extension.extension:
for sub_attribute in dir(sub_extension):
if sub_attribute.startswith("_") or callable(
getattr(sub_extension, sub_attribute)
):
continue
elif sub_attribute == "url":
if (
sub_extension.url == "code"
or sub_extension.url == "codingSystem"
or sub_extension.url == "codeSystemName"
or sub_extension.url == "displayName"
):
print(
f"Finding {counter}: INFERENCE EXTENSIONS: EXTENSION: {sub_attribute.capitalize()}: {sub_extension.url}"
)
elif sub_attribute == "value_string" and sub_extension.value_string is not None:
print(
f"Finding {counter}: INFERENCE EXTENSIONS: EXTENSION: {sub_attribute.capitalize()}: {sub_extension.value_string}"
)
elif attribute == "url" and extension.url is not None:
if extension.url == "section":
print(
f"Finding {counter}: INFERENCE EXTENSIONS: {attribute.capitalize()}: {extension.url}"
)
if __name__ == "__main__":
radiology_insights_sync()
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