Detecting Weakest Stage of Cervical Cancer

Inspiration

We wanted to contribute to a world where incurable diseases are no longer incurable.

What it does

Our software is able to analyze data extracted from cervical cancer cells where we use Python to conduct tests in order to determine the weakest stage in the cell cycle of the cells to help radiation therapy succeed.

How we built it

We used FLIM (Fluorescence Lifetime Imaging Microscopy) software and Anaconda Python notebooks to analyze the data we extracted from cells.

Challenges we ran into

We had a difficult time understanding the accuracy and applicability of our data which is why we ran three different data normality tests which proved that our data was in fact accurate.

Accomplishments that we're proud of

We were able to identify which stage of the cell cycle is the weakest which is quite impactful towards effectively stopping the growth of cancer through radiation therapy.

What we learned

We learned how to effectively use data normality tests to statistically analyze our data in an efficient manner.

What's next for Detecting Weakest Stage of Cervical Cancer

We hope to further analyze other forms of cancer to find effective ways of preventing the growth of cancer in all forms of cancer, not just cervical cancer.

Built With

• flim
• python