Abstract
A form of cancer known as leukemia, attacks the body's blood cells and
bone marrow. This happens when cancer cells multiply rapidly in the bone marrow.
The uploaded image is analyzed by the website, and if leukemia is present, the user is
notified-a collection of pictures depicting leukemia as well as healthy bones and
blood. Once collected from Kaggle, the data is preprocessed using methods like image
scaling and enhancement. To create a Deep Learning (DL) model, we use the VGG-16
model. The processed data is used to “train” the model until optimal results are
achieved. A Hypertext Markup Language (HTML) based website is built to showcase
the model. Using a DL model, this website returns a response indicating whether or not
the user's uploaded photograph shows signs of leukemia. The primary aim of this site is
to lessen the likelihood that cancer cells may multiply while the patient waits for test
results or is otherwise unaware of their condition. Waiting for results after a leukemia
test can cause further stress and even other health problems, even if the person is found
to be leukemia-free. This problem can be fixed if this website is used as a screening
tool for leukemia.