Identify brain tumors
using AI
Below is a free classifier to identify brain tumors. Just upload your image, and our AI will predict if there's a tumor or not - in just seconds.
Upload an MRI of the brain.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("Brain-Tumors-identifier", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/Brain-Tumors-identifier/invoke', {
method: 'POST',
headers: {
'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
'Content-Type': 'application/json',
},
body: JSON.stringify(
{"data": "your_image_url"}
)
})
.then(response => response.json())
.then(data => console.log(data));
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_BEARER_TOKEN" \
-d '{"data": "your_image_url"}' \
https://www.nyckel.com/v1/functions/Brain-Tumors-identifier/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict if there's a tumor or not.
This pretrained image model uses the Tumor Dataset dataset and has 4 labels, including Gilioma Tumor, Meningioma Tumor, Pituitary Tumor, and No Tumor.
We'll also show a confidence score (the higher the number, the more confident the AI model is around if there's a tumor or not).
Whether you're just curious or building brain tumors detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify brain tumors at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Radiology Departments: Screen brain MRI scans to prioritize cases requiring immediate attention. Reduce diagnostic turnaround times and improve patient outcomes through early detection.
- Telemedicine Services: Provide preliminary tumor assessments for remote or underserved areas. Extend specialized care to regions lacking on-site neuroradiology expertise.
- Medical Research: Analyze large datasets of brain MRIs to identify patterns in tumor occurrence. Accelerate research into brain cancer risk factors and potential prevention strategies.
- Neurosurgery Planning: Assist surgeons in pre-operative planning by highlighting tumor locations. Improve surgical precision and reduce procedural risks for brain tumor patients.
- Clinical Trials: Screen potential participants for brain tumor studies more efficiently. Streamline the recruitment process for clinical trials testing new cancer treatments.
- Medical Education: Train new radiologists using AI-assisted tumor detection as a learning tool. Enhance the skills of medical students and residents in identifying brain abnormalities.
- Health Insurance: Support claim processing by verifying brain tumor diagnoses from submitted MRIs. Expedite approvals for necessary treatments and reduce fraudulent claims.