A machine learning model that detects diabetic retinopathy
Upload tumor data to visualize predictions
Detect tumors in brain images
Identify potential diseases from symptoms
Classify medical images into 6 categories
Visualize DICOM files and run AI models for radiation therapy
Ask medical questions and get detailed answers
Classify lung cancer cases from images
Predict eye conditions from OCT images
Upload an image and get a skin lesion prediction
Generate medical advice and treatment plans
Answer medical questions using ClinicalBERT
Predict heart disease risk using health data
Diabetic Retinopathy is a medical condition caused by diabetes that affects the blood vessels in the retina, the light-sensitive tissue at the back of the eye. It can lead to blindness if left untreated. This condition is a common complication of diabetes and occurs when high blood sugar levels damage the blood vessels, causing them to swell, leak, or grow abnormally.
• Machine Learning-Based Detection: The app uses advanced machine learning algorithms to analyze retinal images and detect signs of diabetic retinopathy.
• Severity Prediction: It can predict the severity of diabetic retinopathy, helping in early diagnosis and timely treatment.
• High Accuracy: The model is trained on a large dataset of retinal images to ensure high accuracy in detection and prediction.
• Real-Time Analysis: The app can process retinal images in real-time, providing quick and reliable results.
• Integration with Medical Systems: It can be integrated with existing medical systems for seamless patient data management.
1. What is Diabetic Retinopathy?
Diabetic Retinopathy is a complication of diabetes that damages the blood vessels in the retina, potentially leading to vision loss.
2. How accurate is the Diabetic Retinopathy app?
The app is highly accurate, as it is trained on a large dataset of retinal images and uses advanced machine learning algorithms.
3. Can the app be used for real-time diagnosis?
Yes, the app can process retinal images in real-time, making it a valuable tool for quick and reliable diagnosis.