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.

brain tumors identifier

Upload an MRI of the brain.

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Get started

    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.

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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.

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