Machine Learning Algorithms For Skin Disease Prediction
Keywords:
textures, colorsAbstract
Dermatology is the study and treatment of skin problems. These problems can vary depending on
where you are and what season it is because of differences in weather. Human skin is complex,
with many different textures, colors, and other features, making it difficult to understand and
study.Despite many studies focusing on using computer vision to understand skin, not many have
looked at it from a medical perspective. In rural areas where there aren't many doctors, people
often ignore skin problems until they get worse.That's why there's a need for a reliable way to
automatically detect skin diseases. So, we created a deep learning model, which is a type of
machine learning, to tell the difference between healthy skin and skin with problems. Our model
can also classify different types of skin diseases, like basal cell carcinoma or melanocytic
nevi.Deep learning lets us train our model using large amounts of data quickly. This helps the
computer learn how to make accurate predictions about skin problems. We used a type of deep
learning called Convolutional Neural Networks (CNNs) because they're good at categorizing
pictures. This technology helps support and improve the field of dermatology.
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.













