Inspiration
This research would help organizations, working in the health sector, especially in cancer studies.
What it does
The main problem of the project is to detect breast cancer based on a set of features calculated from a digitized image of the Fine Needle Aspiration (FNA) of a breast mass from a patient. Diagnosis (M = malignant, B = benign)
How we built it
We have built this project by using Python language and extracting the data set.
Challenges we ran into
In the beginning we got few errors while predicting the values that are taken from the dataset and later we resolved it.
Accomplishments that we're proud of
Finally we got that our project can be applied in breast cancer diagnosis to improve the accuracy and therefore assist early diagnosis of breast cancer.
What we learned
We have learned the Classification Accuracy method to find the accuracy of our models. It is the ratio of number of correct predictions to the total number of input samples.
What's next for Breast Cancer Prediction
This prediction and recommendation system can help doctors to diagnose and cure the disease more efficiently.
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