Human skin is the largest organ in our body which provides protection against heat, light, infections and injury .The number of cases of melanoma skin cancer has been increasing year by year. Since doctors need to diagnosis the skin cancer manually there will be some or the other human error therefore to overcome such problems we have developed this project which is done using machine learning technique and the results are obtained accurately and efficiently.
Currently skin cancer is being detected by doctors by manually checking the pattern and area of affected area. Since this method is time consuming and is prone to human errors, research is being conducted to detect skin cancer automatically. Image Processing techniques are extensively being used for the purpose. However due to limitation of Image Processing where in certain parameters have to be sent manually, this approach for automated detection turns out practically to be inefficient and thus it would be apt to train the machine to identify the cancer areas without using complex algorithms, which in turn increases the accuracy and efficiency.
As patients goes for diagnosis it is obvious that there will be some or the other human errors. So it can be used as a second opinion which serves as a boon for the doctors as well as patients who goes for skin cancer diagnosis.
It's simple and easy especially very useful for doctors where they need to diagnosis more number of patients. Also for the first time cubic regression is used in this project.
India's Sustainable Development
As already said it is easy to implement and not time consuming no need of any investments, one should have minimum computer knowledge and has to know about basic matlab. Since doctors need to diagnosis the skin cancer manually there will be some or the other human error therefore to overcome such problems we have developed this project and the results are obtained accurately and efficiently which serves the society
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