In the early 1990’s, William Wolberg and his associates at
the University of Wisconsin published a near 700-sample dataset of breast
cancer masses. These masses had been biopsied via fine needle aspirates.
Doctors then rated nine inputs such as clump thickness, uniformity of cell
shape, bland chromatin and mitoses on a scale of one to ten, one meaning the
trait was indicative of a benign mass and ten meaning the trait was indicative
of a malignant tumor. This data was then published to the University of
California Irvine’s Machine Learning Repository as public domain. I am grateful
for access to this data, as it provided my networks with training experiences
and testing banks. The data also proved very suitable for classification
I would also like to acknowledge my A.P. Computer Science
teacher, Mrs. Barrett. Before taking her class sophomore year, I programmed
everything in C#. I am now confident in my java skills and have applied
knowledge gained from her class to this project.
When ABC 7 asked to run a story on my project, I was flattered
and very excited. The reporter Fallon Silcox did an amazing job with the story.
I want to thank the ABC team, especially Jason Wildenstein, for granting me the
rights to embed the video in my Google application.
Finally, I would like to thank my family for their continued support without which none of this would have been possible.