Classify MRI images to detect brain tumors
Classify and assess severity of lung conditions from chest X-rays
Generate medical reports from patient data
Visualize DICOM files and run AI models for radiation therapy
Predict diabetes risk based on medical data
Answer medical questions using ClinicalBERT
Answer medical questions using real-time AI
Upload tumor data to visualize predictions
Upload EEG data to classify signals as Normal or Abnormal
Store and analyze lung sounds
Identify potential diseases from symptoms
Classify medical images into six categories
Classify lung cancer cases from images
The Brain Tumor Classifier is a cutting-edge AI-powered tool designed to analyze MRI images for the detection and classification of brain tumors. It leverages advanced machine learning algorithms to provide accurate and reliable results, aiding healthcare professionals in early diagnosis and treatment planning.
• Accurate MRI Image Analysis: The tool is trained on a large dataset of MRI images to detect abnormalities and classify tumors with high precision.
• User-Friendly Interface: Designed for ease of use, the platform allows seamless upload and analysis of MRI scans.
• Fast Processing: Provides quick results, enabling timely medical decisions.
• Multi-Modal Compatibility: Supports various types of MRI scans, including T1, T2, and FLAIR images.
• Data Privacy: Ensures secure handling of patient data in compliance with medical regulations.
What types of MRI scans does the Brain Tumor Classifier support?
The classifier supports T1-weighted, T2-weighted, and FLAIR MRI images for accurate tumor detection.
How accurate is the Brain Tumor Classifier?
The tool achieves high accuracy due to its training on a large and diverse dataset of brain MRI scans, but it should be used as a diagnostic aid alongside professional medical judgment.
Is patient data secure when using the classifier?
Yes, the platform adheres to strict data protection guidelines, ensuring all patient information remains confidential and secure.