Detecting Cancer with ML

Inspiration

My inspiration came from learning about struggles with detecting cancer and other health issues. I love computer science and am actively learning machine learning, so I decided that the 2 fields can combine for the better.

What it does

My project simply outputs a probability of having breast cancer given certain data points. There is no X-rays required!

How I built it

I used sklearn, a ML library and specifically linear regression to train a model to detect breast cancer.

Challenges we ran into

Some challenges were that the data needed to be encoded effectively. I had to use one-hot encoding to turn some categorical data into numerical data.

Accomplishments that we're proud of

I am proud of how robustly the final result turned out, especially with the accuracy and training time.

What we learned

I learned why using one-hot encoding is useful in some scenarios, and that not all tasks necessarily need a neural network.

What's next for Detecting Cancer with ML

In the future, I plan to expand this project to detect more types of cancer and disease. I also want to incorporate different types of ML for greater accuracy. Finally, I want to deploy this to be used in real-world scenarios and offices.

Built With

• python
• sklearn