Complete API documentation for OptiMediX integration
/api/v1/analysis/pneumonia
Analyze chest X-ray for pneumonia detection
image
filerequiredChest X-ray image (JPEG, PNG, DICOM)
patient_id
stringrequiredUnique patient identifier
curl -X POST "https://api.optimedix.ai/v1/analysis/pneumonia" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: multipart/form-data" \
-F "image=@chest_xray.jpg" \
-F "patient_id=P12345"
Successful analysis
{
"prediction": "pneumonia",
"confidence": 0.95,
"regions_of_interest": [
{
"x": 120,
"y": 150,
"width": 100,
"height": 100
}
],
"processing_time": "1.2s"
}
Invalid input
{
"error": "Invalid image format"
}
/api/v1/patients/{id}
Retrieve patient information and medical history
id
stringrequiredPatient's unique identifier
curl -X GET "https://api.optimedix.ai/v1/patients/P12345" \
-H "Authorization: Bearer YOUR_API_KEY"
Patient data retrieved successfully
{
"id": "P12345",
"name": "John Doe",
"medical_history": [],
"recent_analyses": []
}
Patient not found
{
"error": "Patient not found"
}
/api/v1/patients/{patient_id}/history
Retrieve patient's analysis history
patient_id
stringrequiredUnique patient identifier
from_date
stringFilter results from this date (YYYY-MM-DD)
curl "https://api.optimedix.ai/v1/patients/P12345/history" \
-H "Authorization: Bearer YOUR_API_KEY"
Successfully retrieved history
{
"patient_id": "P12345",
"analyses": [
{
"id": "A789",
"type": "pneumonia_detection",
"result": "positive",
"confidence": 0.95,
"date": "2024-03-15T14:30:00Z"
}
]
}
import optimedix
client = optimedix.Client('YOUR_API_KEY')
# Analyze an image
response = client.analysis.detect_pneumonia(
image_path='chest_xray.jpg',
patient_id='P12345'
)