Krisshvamsi/Skin-Disease-Identification-Using-Image-Analysis
The project deals with Detecting skin diseases based on images. The model has been implemented using Python and Convolutional Neural Networks and OpenCV. The approach works on color images and greyscale images. Used different Neural Network layers such as Max-Pooling, Flatten, Conv2D, etc. to build a system that successfully detects skin diseases based on images captured through camera and deployed model using flask application and web development technologies. Received Silver Award at Ennovate-The International Innovation Show-2021, Poland for this innovation
This project helps medical practitioners, especially in rural areas, or individuals who are hesitant to seek immediate medical consultation, to quickly identify potential skin diseases. You input an image of a skin condition, and the system processes it to predict the type of skin disease. This is designed for healthcare providers in clinics, or anyone needing an initial screening for dermatological issues.
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Use this if you need an automated, initial screening tool to identify common skin diseases from an image, particularly in settings where immediate access to a dermatologist is limited.
Not ideal if you require a definitive medical diagnosis, as this tool provides an initial prediction and is not a substitute for professional medical consultation.
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Jul 13, 2021
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