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# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
"""
FILE: sample_complete_order_discrepancy_inference.py
DESCRIPTION:
The sample_complete_order_discrepancy_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 Complete Order Discrepancy order type,
-the missing body parts, and
-the missing body part measurements
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_complete_order_discrepancy_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 = """CLINICAL HISTORY:
20-year-old female presenting with abdominal pain. Surgical history significant for appendectomy.
COMPARISON:
Right upper quadrant sonographic performed 1 day prior.
TECHNIQUE:
Transabdominal grayscale pelvic sonography with duplex color Doppler and spectral waveform analysis of the ovaries.
FINDINGS:
The uterus is unremarkable given the transabdominal technique with endometrial echo complex within physiologic normal limits. The ovaries are symmetric in size, measuring 2.5 x 1.2 x 3.0 cm and the left measuring 2.8 x 1.5 x 1.9 cm.\n On duplex imaging, Doppler signal is symmetric.
IMPRESSION:
1. Normal pelvic sonography. Findings of testicular torsion.
A new US pelvis within the next 6 months is recommended.
These results have been discussed with Dr. Jones at 3 PM on November 5 2020."""
# Create ordered procedure
procedure_coding = models.Coding(
system="Http://hl7.org/fhir/ValueSet/cpt-all",
code="USPELVIS",
display="US PELVIS COMPLETE",
)
procedure_code = models.CodeableConcept(coding=[procedure_coding])
ordered_procedure = models.OrderedProcedure(description="US PELVIS COMPLETE", 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_complete_order_discrepancy(radiology_insights_result)
except Exception as ex:
raise ex
def display_complete_order_discrepancy(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.COMPLETE_ORDER_DISCREPANCY:
print(f"Complete Order Discrepancy Inference found")
ordertype = ri_inference.order_type
for coding in ordertype.coding:
print(f"Complete Order Discrepancy: Order Type: {coding.system} {coding.code} {coding.display}")
if not ri_inference.missing_body_parts:
print(f"Complete Order Discrepancy: Missing Body Parts: empty list")
else:
for missingbodypart in ri_inference.missing_body_parts:
for coding in missingbodypart.coding:
print(
f"Complete Order Discrepancy: Missing Body Part: {coding.system} {coding.code} {coding.display}"
)
if not ri_inference.missing_body_part_measurements:
print(f"Complete Order Discrepancy: Missing Body Part Measurements: empty list")
else:
for missingbodypartmeasurement in ri_inference.missing_body_part_measurements:
for coding in missingbodypartmeasurement.coding:
print(
f"Complete Order Discrepancy: Missing Body Part Measurement: {coding.system} {coding.code} {coding.display}"
)
if __name__ == "__main__":
radiology_insights_sync()
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