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# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
"""
FILE: sample_radiology_procedure_inference.py
DESCRIPTION:
The sample_radiology_procedure_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 Procedure code,
- the Imaging Procedure anatomy and modality,
- Ordered Procedure code and description
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_radiology_procedure_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 = """
Exam: Head CT with Contrast
History: Headaches for 2 months
Technique: Axial, sagittal, and coronal images were reconstructed from helical CT through the head without IV contrast.
IV contrast: 100 mL IV Omnipaque 300.
Findings: There is no mass effect. There is no abnormal enhancement of the brain or within injuries with IV contrast.\
However, there is no evidence of enhancing lesion in either internal auditory canal.
Impression: Negative CT of the brain without IV contrast.
I recommend a new brain CT within nine months."""
# Create ordered procedure
procedure_coding = models.Coding(
system="Https://loinc.org",
code="24727-0",
display="CT HEAD W CONTRAST IV",
)
procedure_code = models.CodeableConcept(coding=[procedure_coding])
ordered_procedure = models.OrderedProcedure(description="CT HEAD W CONTRAST IV", 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_radiology_procedure(radiology_insights_result)
except Exception as ex:
raise ex
def display_radiology_procedure(radiology_insights_result):
for patient_result in radiology_insights_result.patient_results:
for ri_inference in patient_result.inferences:
if ri_inference.kind == models.RadiologyInsightsInferenceType.RADIOLOGY_PROCEDURE:
print(f"Radiology Procedure Inference found")
for proccod in ri_inference.procedure_codes:
print(f"\nRadiology Procedure: PROCEDURE CODES:")
for coding in proccod.coding:
print(
f"Radiology Procedure: PROCEDURE CODES: Code: {coding.system} {coding.code} {coding.display}"
)
for improc in ri_inference.imaging_procedures:
print(f"\nRadiology Procedure: IMAGING PROCEDURE:")
for attribute in improc:
if (
hasattr(improc, attribute)
and not attribute.startswith("_")
and not callable(getattr(improc, attribute))
):
if attribute == "anatomy":
if improc.anatomy is not None:
for coding in improc.anatomy.coding:
print(
f"Radiology Procedure: IMAGING PROCEDURE: Anatomy Code: {coding.system} {coding.code} {coding.display}"
)
else:
print(f"Radiology Procedure: IMAGING PROCEDURE: Anatomy: none")
elif attribute == "modality":
if improc.modality is not None:
for coding in improc.modality.coding:
print(
f"Radiology Procedure: IMAGING PROCEDURE: Modality Code: {coding.system} {coding.code} {coding.display}"
)
else:
print(f"Radiology Procedure: IMAGING PROCEDURE: Modality: none")
ordered_procedure = ri_inference.ordered_procedure
print(f"\nRadiology Procedure: ORDERED PROCEDURE:")
if ordered_procedure.description is not None:
print(f"Radiology Procedure: ORDERED PROCEDURE: Description: {ordered_procedure.description}")
if ordered_procedure.code is not None:
for coding in ordered_procedure.code.coding:
print(
f"Radiology Procedure: ORDERED PROCEDURE: Code: {coding.system} {coding.code} {coding.display}"
)
if __name__ == "__main__":
radiology_insights_sync()
|
