Diabedect
10+
Downloads
Everyone
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About this app
Introducing Diabedect: Your Advanced Diabetic Retinopathy Detection and Management App
Diabedect is a cutting-edge mobile application designed to revolutionize the detection and management of diabetic retinopathy, a leading cause of vision loss among individuals with diabetes. Leveraging state-of-the-art machine learning algorithms, Diabedect analyzes retinal images with unparalleled accuracy and efficiency.
Diabedect integrates datasets from prestigious competitions such as APTOS 2019 Blindness Detection and the 2015 Diabetic Retinopathy Detection Competition hosted on Kaggle, ensuring accurate and comprehensive analysis. By harnessing the power of these datasets and cutting-edge Convolutional Neural Networks (CNN) technology, Diabedect sets a new standard in Diabetic Retinopathy diagnosis.
Key Features:
• Advanced Diabetic Retinopathy Detection: Diabedect utilizes deep learning techniques to analyze retinal images and identify diabetic retinopathy indicators with precision and reliability.
• Ophthalmologist Interface: For healthcare professionals, Diabedect offers a user-friendly interface to upload retinal images of patients, facilitating swift and accurate detection of diabetic retinopathy indicators. The app generates reports which help ophthalmologists to make informed clinical decisions.
• Patient Interface: Patients can access the services of trusted ophthalmologists who utilize Diabedect for Diabetic Retinopathy Detection. Patients can access personalized reports through Diabedect's intuitive patient interface. With detailed insights into Diabetic Retinopathy Detection results, patients can take proactive steps towards managing their eye health effectively.
• Real-time Report Delivery: Diabedect enables ophthalmologists to send real-time reports to patients, fostering seamless communication and collaboration between healthcare providers and patients.
Classification Report Insights:
The overall accuracy of Diabedect stands at 80%, indicating strong alignment between the model's predictions and the actual labels in the test dataset.
Diabedect represents a significant advancement in diabetic retinopathy detection, empowering both healthcare professionals and patients to prioritize and manage their health effectively.
Diabedect is a cutting-edge mobile application designed to revolutionize the detection and management of diabetic retinopathy, a leading cause of vision loss among individuals with diabetes. Leveraging state-of-the-art machine learning algorithms, Diabedect analyzes retinal images with unparalleled accuracy and efficiency.
Diabedect integrates datasets from prestigious competitions such as APTOS 2019 Blindness Detection and the 2015 Diabetic Retinopathy Detection Competition hosted on Kaggle, ensuring accurate and comprehensive analysis. By harnessing the power of these datasets and cutting-edge Convolutional Neural Networks (CNN) technology, Diabedect sets a new standard in Diabetic Retinopathy diagnosis.
Key Features:
• Advanced Diabetic Retinopathy Detection: Diabedect utilizes deep learning techniques to analyze retinal images and identify diabetic retinopathy indicators with precision and reliability.
• Ophthalmologist Interface: For healthcare professionals, Diabedect offers a user-friendly interface to upload retinal images of patients, facilitating swift and accurate detection of diabetic retinopathy indicators. The app generates reports which help ophthalmologists to make informed clinical decisions.
• Patient Interface: Patients can access the services of trusted ophthalmologists who utilize Diabedect for Diabetic Retinopathy Detection. Patients can access personalized reports through Diabedect's intuitive patient interface. With detailed insights into Diabetic Retinopathy Detection results, patients can take proactive steps towards managing their eye health effectively.
• Real-time Report Delivery: Diabedect enables ophthalmologists to send real-time reports to patients, fostering seamless communication and collaboration between healthcare providers and patients.
Classification Report Insights:
The overall accuracy of Diabedect stands at 80%, indicating strong alignment between the model's predictions and the actual labels in the test dataset.
Diabedect represents a significant advancement in diabetic retinopathy detection, empowering both healthcare professionals and patients to prioritize and manage their health effectively.
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Data is encrypted in transit
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What's new
Initial Release
App support
About the developer
Rafah Ahmed
rafah.ahmed@cust.edu.pk
Pakistan
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